Journal of Forensic Vocationology Vol. 7, Issue 1.
Journal of Forensic Vocationology Vol. 7 (1) Monograph
[Note from the Editors: Permission to Reprint this Monograph of selected materials from JOFV Volume 7(1), Fall 2002, © 2002 by Vocationology, Inc., granted by the Editors of the JOFV for inclusion on the IARP Fall Conference 2003 Disk].
(2003 by Vocationology, Inc.
This JOFV Monograph includes the following Annotated Articles with minor updates:
Page - Title - Author(s)
3 Product Peer Review of Course Disk 1: The Updating of the 5th Edition DOT - Grimley
4 Product Peer Review on MVQS2003 - Streater
5 Frequently asked questions regarding the MVQS 2001-2003 Programs - McCroskey
8 The McCroskey Vocational Quotient System (MVQS) Theory of Transferable Skills: Revised, Extended and Updated for the 21st Century - McCroskey, Grimley, Williams, Hahn, Lowe, Wattenbarger, Stein & Dennis
31 The MVQS Vocational Interest and Personality Reinforcer (VIPR) Job-based Personality Type Indicator and MTSP[1] Jobs-Based Vocational Interest Personality Types Crosswalk to Jung People-Based Personality Types - McCroskey, Hahn, Streater, Sinsabaugh, Mayer, Van de Bittner, Lowe & Dennis
91 Emotional Trauma: Its Impact on Vocational Analysis - McCroskey & Dennis
104 MTSP VQ1-OES Aggregate & VQ1-McDOT Specific Wage Estimation - McCroskey, Hahn & Dennis
132 MTSP VQ1-OES Aggregate & VQ1-McDOT Specific Wage Estimation Follow-Up Study – McCroskey, Hahn, Dennis & Wattenbarger
Note from the Editors: The Journal of Forensic Vocationology is a private, copyrighted, scientific, research-oriented Journal, published periodically (typically 1 time per year) by Vocationology, Inc. Articles considered for inclusion are subject to Peer-Review and Editorial review prior to inclusion in the Journal. Co-Editors: Billy J. McCroskey, Ph.D. & William E. Wattenbarger, Ph.D. (763-569-0680)
The primary purpose of the Journal of Forensic Vocationology is to disseminate scientific research and related information deemed relevant to the field of Vocationology (See definition in The Journal of Vocationology, Vol. (1) 1, 1995) and related disciplines including: Psychology, Student Personnel Services, Career Development, Rehabilitation Economics, Rehabilitation Counseling, Job Analysis, Worker Trait-Factor Theory, Vocational Evaluation and Work Adjustment. From time to time, research & informational articles may be invited or solicited from recognized experts in Vocationology and Related fields.
The Editorial Advisory Board and Peer Review Committee
Kenneth Dennis, Ph.D., LP, LMFT, CRV, Associate Editor -MN - ken.dennis@
Robert Male, Ph.D., CEA - OR - bobmale@
Steve Hahn, M.S., CVE, CRC, QRC, Associate Editor - MN - sjhahn1@
David Stein, Ph.D., ABVE - NV - DBSPHD@
Scott Streater, D.V.S, ABVE - NC – sesdvs@
Judith Harper-Haley, M.R.C., ABVE - TX - london_suede@email.
Craig Feldbaum, Ph.D., LP, ABVE - LA - cfeldb@gulfsouth.
Claude Peacock, M.S., ABVE - AL - cfpeacock@
David Toppino, M.A., CVE, CEA, ABVE - CA - veala@
John Williams, D.Ed., ABVE - FL - amwfl@
Lyndette Mayer, Ph.D., ABVE - NC - lindphd@
Jan Lowe, MA, CRC, ABVE - MN - redfanjan@
Cynthia Grimley, MS, ABVE - SC - cpgrimley@
Nat Fentress, MS, ABVE - LA - nfrehab@worldnet.
Ron Smolarski, MS, CEA, CLCP - MI - ron@
Larry L. Sinsabaugh, Ph.D., LMFT - l.l.sinsabaugh.phd@worldnet.
Billy J. McCroskey, Ph.D., CRE, CRC, CRV, ABVE, Co-Editor
Dr. McCroskey is currently the President of Vocationology, Inc., located at 8209 Halifax Court North, Brooklyn Park, MN, 55443. He was the Founding Editor of the Northwest Georgia Rehabilitation Counselor Newsletter, The Vocationologist, the Journal of Vocationology, and the Journal of Forensic Vocationology. Dr. McCroskey spends approximately 50% of his time engaged in scientific research relating to the prediction starting and average wage. He was the original developer and senior author of the Vocational Diagnosis and Residual Employability (VDARE) Process. He has engaged in many years of research leading to development of the McCroskey Vocational Quotient (VQ), the DataMaster Job-Person Matching Program Series and the MVQS McDOT, McPLOT and MTSP 2001 series of Worker Trait Factor Job-Person Matching Programs and Earning Capacity Prediction Systems. In 2002 he received the David S. Frank ABVE Lifetime Achievement Award. Ph 763-569-0680, e-mail: bjmccroskey@.
In his research, Dr. McCroskey has developed and updated more than 3,247 National, State, County, Parish, Province and Borough Job Bank Databases of frequently-hired-for jobs. Dr. McCroskey’s Job Person Matching and Earning Capacity Systems have been peer-reviewed in four Comparison of Job Person Matching Systems Publications (Botterbusch, 1983 & 1986; McDaniels, et. al., 1994; and Dennis & Dennis, 1998).
Dr. McCroskey is a Lifetime Certified Diplomate Level ABVE Vocational Expert, a Certified Rehabilitation Counselor (CRC), a Certified Rehabilitation Vocationologist (CRV) and a Lifetime Certified Rehabilitation Economist (CRE). He is a graduate of the University of Georgia and a life member of both the American Board of Vocational Experts (ABVE) and the American Rehabilitation Economic Association (AREA).
Dr. McCroskey has presented White Papers on the Predictive Validity of the Vocational Quotient at several National Conferences. He currently specializes in Pre/Post Injury Employability Evaluations and Earning Capacity Determinations. Dr. McCroskey has worked on 5,000+ cases involving Individualized Vocational Rehabilitation Planning, Medical Case Management, Job Placement, Job Analysis, Earning Capacity, Workers Compensation, Rehabilitation Economic Past Wage Loss and Future Diminution of Earning Capacity, Personal Injury, Wrongful Death, Harassment, Discrimination, Divorce and Social Security. E-mail - bjmccroskey@
William E. Wattenbarger, Ph.D., CRC, CRV, Co-Editor
Dr. Wattenbarger hails from Epworth, GA. He has served as Co-Editor for The Vocationologist, the Journal of Vocationology and the Journal of Forensic Vocationology since their inception. He is President of Rehabilitation Innovation, Inc. He currently works as a Rehabilitation Counselor in North Central Georgia. In the past, he has worked as a Supervisor at the Roosevelt Warm Springs Institute, in Warm Springs, GA.
Dr. Wattenbarger is a computer programmer extraordinaire. He provided the programming skills and consultation necessary to bring the original McDOT, McPLOT, and MTSP series of Programs to fruition. Dr. Wattenbarger co-developed and co-authored the VDARE Process. He designed the website. He enjoys family time and working quietly behind the scenes. Ph: 706-846-3470, email: wewatt@.
Journal Motto: When worker capacities equal or exceed job demands, employability and earning capacity exist. (BJM, 1981).
Abstracts for all articles in the first five issues of the Journal of Forensic Vocationology (JOFV) are available at our Internet Web Site: . If you would like to contribute to this scientific, research-oriented, national peer-reviewed Journal, let us know at our address below. Manuscripts submitted for peer-review and publication consideration should be provided to us on a 3 1/2 inch disk, or via e-mail attachment, in standard APA style, preferably in a Word for Windows 97, or Word 2000, word processing document file.
Dr. Billy J. McCroskey, President
Vocationology, Inc.
8209 Halifax Court North
Brooklyn Park, MN 55443-2538
Phone: (763) 569-0680, or (763)-560-7072
e-mail: bjmccroskey@
Past issues of the JOFV (Volumes 1-6) have been electronically published in Word-97 or Word 2000 format and are available for purchase (from Dr. Billy J. McCroskey) on the 30-Hour CEU Course Disk 1: The Updating of the Fifth Edition DOT (McCroskey & Dennis, 2000) as well as well as on three other training Course Disks available for purchase thru Vocationology, Inc., at $165.00 each, including S & H. However you got it, you are now reading from the Spring 2002 issue of the Journal of Forensic Vocationology Vol. (7), Issue 1. If you are intrigued with the research, theory and practice-related article in this issue and wish to obtain one or more of the electronically published back issues of the JOFV, let us know by e-mail at bjmccroskey@ and we'll try to accommodate your wish. Enjoy.
Sample Product Peer Reviews
Product Peer Review
By
Cynthia P. Grimley, MS, CRC, CCM, ABVE
On
The Updating of the 5th Edition DOT
A 30-Hour CEU Course
Authors: Billy J. McCroskey Ph.D., CRC, CRE, CRV, ABVE
Kenneth L. Dennis, Ph.D., LP, CRC, CRV, LMFT
The U.S. Department of Labor, Employment and Training Administration published the Fourth Edition, Revised 1991 of the Dictionary of Occupational Titles (DOT). The U.S. Department of Labor has no scheduled plan to update the DOT again. The current research conducted by the U.S. Department of Labor is geared towards the O*NET, which currently has limitations as admitted by the government. The 4th Edition DOT is outdated. It is now up to the private sector to update and coordinate both of these resources. The McCroskey Vocational Quotient System Programs, (MVQS) McDOT, McPLOT and MTSP 2000) has done exactly this.
The text to begin the training and understanding of the MVQS 2000 Program Series (McCroskey, 2000) has been developed. The 30 CEU Credit Course on The Updating of the 5th Edition DOT details data fusion research to produce updated job analysis profiles for all 12,775 specific jobs in the McDOT 2000 and related job-person matching software. The course also includes a fully developed, 45 page, Case Study Report with attachments. The course is copyrighted so you are unable to print any of the information except the Case Study Report. This is a CD-ROM based course, which runs off the DAC II Engine. This is compatible for all IBM PC’s and those with 100 percent compatibility. The DAC II Engine will require 12.6 mb on your hard drive. The course itself will take up 20 MB of hard drive space.
The course installs with ease. After you enter your student registration data information and begin the course you may exit any time you wish. When you return, the course will automatically pick up where you left off. There are hypertext words underlined that enable you to click on to obtain the definitions and related information. The course features colorful and comical graphics that highlight the material. The course contains eleven chapters:
1) Introduction,
2) Using McDOT, McPLOT, & MTSP 2000,
3) Expert Testimony,
4) Statistical Foundations Relating to Daubert,
5) Part 1: O’NET Validity under Daubert,
6) Part 2: O’NET Validity Under Daubert,
7) VDARE, O’NET 98 & MVQS Theoretical Basis,
8) O’NET 98 Transferable Skills (TS) Paradigm,
9) MVQS McDOT 2000 Contributions,
10) References & Bibliography: A-L,
11) References & Bibliography: M-Z.
As a bonus the CD-ROM Course contains the first five peer-reviewed Journals of Forensic Vocationology (Vols. 1-5), a $250.00 value, which serve as the course text. These Journals are full of scientific research articles, which vocational experts are increasingly in dire need of, when questioned under the Daubert Standards. The Updating of the 5th Edition DOT and the five peer-reviewed Journals of Forensic Vocationology are available for $150.00 plus $15 for shipping and handling. This course is the first in a five part series. For ordering information, contact Dr. Billy J. McCroskey, Vocationology, Inc., 8209 Halifax Court North, Brooklyn Park, MN 55443. Phone: 612-569-0680 or 763-569-0680.
DLU: 08/7/2000
MVQS 2003, 6th Edition Product Peer-Review
I recently purchased the McCroskey Vocational Quotient System (MVQS 6.0, McCroskey, 2003) and the accompanying 6th Edition Dictionary of Occupational Titles (McDOT 6.0). This system, which was developed and authored by Dr. Billy J. McCroskey, is a refreshing evolution from his former programs. I have owned McCroskey reference materials and have copies of all of his systems since 1980. I have also used the old manual system (VDARE), prior to the purchase of my first computer in 1983. I have seen the ROC, his first system, but have never utilized it in the field. All of these systems take the guesswork and much of the argument out of reasonable career choices, worker capacity, employability and earning capacity. My statement is based on the fact that they are all empirically based, and since their inception, have been able to meet the Daubert Standards, years before they were handed down from the US Supreme Court. Both McCroskey’s works and the Daubert Standards rely on scientific research and standardized measurement. With MVQS 6.0, you are able to produce solid findings that can lead to well researched opinions, which in turn aids in formulation of your opinions and conclusions to form a solid basis for good reports and sound testimony. This programs meet all of the requirements set forth for Judges by the 2000 reference entitled, Reference Manual on Scientific Evidence, published by the Federal Judicial Center and available on the internet. Structuring a report with the data from this program, according to the directions of this legal reference, will provide valid data on an empirical platform to make decisions, in language the Judges have been instructed to look for. What more of a winning combination would one want?
McCroskey’s 6th Edition McDOT is masterfully conceived and constructed, accommodating the 1998-2002 O-Net data and all of the updated US DOL Crosswalks including the SOC, NAICS, CENOCC, OESSOC, ONETSOC, and the Canadian NOC. In my opinion, McCroskey 2003 programs can be used by Vocational Experts in: Social Security Hearings, Workers Compensation, Personal Injury, Divorce or Dissolution, or any other venue that requires reliable vocational measurement and earning capacity estimation.
In contrast to his former programs, MVQS 2003 is still complex, yet far simpler to run and to interpret. It is a dream to load, as it is now totally contained on one computer disk (CD-Rom). The loading is a two-step process, involving the program and job bank databases all emanating from a single disk. Another of the real steps forward is the program has been adapted to a Microsoft Windows( Access 2000 platform. This makes for truly simple to interpret screens and greatly simplified operation. The built in help screens, and the notes “stashed” behind the Help buttons are clearly instructive to the newcomer, both inexperienced and seasoned. In my opinion, the best visual aspect to this program are the screens, which are displayed in a simple-to-read format, without a myriad of confusing data to dazzle the eye and confuse the mind.
The built in set of sample “client” cases gets things off and running with the easy introduction of a “person” into the system as a trial subject. These take the inputs out of the user's responsibility; yet still allow the flexibility of selected changes in values on worker trait inputs or test/subtest values. The relevant sections of the internal manual help screens can be “pulled up” and referenced without confusing eye and head movements. Everything is there on the screen, all in one place, with no distractions.
There is an absence of the old “necessary savvy” to run the programs. I believe anyone can learn to operate the programs. One must know something about the inputs utilized and certainly one must know and understand and be able to explain basic measurement concepts to be able to put this information into a formal report or expert witness testimony. This is also true of the new MVQS Rehabilitation Economist.
All in all, I think this is the best effort I have ever seen in a program such as this and I can’t wait to get a few cases under my belt and write one of the first technical articles on the McCroskey 2003. Bill McCroskey and those involved in “the backroom” should be commended on this magnificent undertaking. This was I’m sure, a massive task, at great expense, with much work and learning involved. To be available at the very competitive rate that it is selling for makes it an “absolute tool” if one is to provide vocational forensic opinions with reasonable certainty based on good science in this modern age. (DLU: 09/24/02)
( Scott Streater, D.V.S.
47 Skyline Road, Southern Shores, North Carolina 27949-3600
(252) 255-1854 Phone or FAX or email: : - sesdvs@
Frequently Asked Questions (FAQ) Regarding MVQS 2001-2003 Programs
1. How do you identify the salient physical and mental requirements of jobs profiled in McDOT?
Answer: We identify the salient physical and mental requirements of jobs from the McCroskey Dictionary of Occupational Titles – 6.0 Edition (McDOT, McCroskey, 2003). The computerized, Windows(TM) Access 2000 based, McDOT Program was modeled after the US DOT, 4th edition revised. The date of last update (DLU) for all profiles of job demands/worker trait requirements in McDOT 2003 was Year 2002. McDOT 2003 job requirement profiles were data mined from the 75 most vocationally significant O*NET identified worker trait job requirement element variables for which means data job requirement profiles were collected and provided for each of 1,122 Occupational Unit (OU) Classification Code Groups (ONET Code Groups). This was necessary in order to bridge the gap between the outdated US 4th edition and the updated job demand/worker trait requirement profiles in the McDOT 6th edition DOT.
2. What type scales, or ratings, exist for measuring these variables?
Answer: The reference for the Job Analysis Scales used to profile jobs in the McDOT 2003 program is the 1991 US HAJ-R. The only major difference is that McDOT incorporates ascending, vs. descending Aptitude Scales (e.g., the higher the scale level, the greater the job demand; i.e., instead of 1=high & 5=low, McDOT aptitude scales are interpreted as 1=low & 5=high) otherwise the JA Scales are the same.
3. How do you address issues of validity and reliability?
To bridge the gap from the outdated 4th edition US DOT to the updated McDOT 6th edition DOT, O*NET-98 Mean job requirements data from the 75 most salient physical and mental worker trait requirement elements (52 ability elements on 8-point scales and 23 work context elements on 5 point scales), were data mined from the 483-variable O*NET ascending scale means data profiles. These data were converted, via multiple regression studies, to the more familiar 1972-91 HAJ-R job analysis scales, to reflect the 24 most vocationally salient physical, mental and environmental worker traits. The data were combined, through data fusion, from element level data, to the worker trait level data, for ease of understanding. In other words, job demand profiles in McDOT 2003 are presented in terms job requirement scales from the 1991 US Revised Handbook for Analyzing Jobs, which are most familiar to SSA ALJs and knowledgeable Vocational Experts, who have grown accustomed to the structure of the 1977 and 1991-Revised, US DOT.
The SVP component, which was missing in the O*NET means data profiles, has been reconstructed and added back to the McDOT job specific data in order for Administrative Law Judges (ALJs) and Vocational Experts to continue to be able to differentiate between unskilled, semi-skilled, and skilled jobs, as well as complete reliable, valid transferable skills analyses (Grimley, et. al., 2000a, 2000b).
4. Has scientific research been published in professional peer-reviewed publications?
Answer: Yes, in many journals, monographs and technical manuals (e.g., the MVQS 2001 Resource Manual) regarding the issues relating to validity and reliability for the MVQS programs employability and earning capacity predictions. The seven issues of the JOFV (Volumes 1-7) on the MVQS 2003 Program Installation Disk in the Journals Subdirectory contain a great deal of the scientific research, independent replication and cross-validation studies attesting to the reliability and validity of the MVQS programs. Other peer-reviewed journals in which some of the research has been published include: the American Board of Vocational Experts Journal of Forensic Vocational Analysis and The Earnings Analyst Journal of the American Rehabilitation Economics Association. Three-way & 5-way inter-rater reliability has been established for MVQS Programs to be very high (Rxxx=0.99). The transferable skills paradigm has been tested and found to be very valid relative to a criterion N of 93 Vocational Experts (Grimley, et. al., 2000a, 2000b). In our opinion, in the hands of a trained Vocational Expert, MVQS programs are underpinned with more than enough scientific research, which has been peer-reviewed and published, to meet or exceed the standards for expert witness testimony set fourth in the US Supreme Court in their Daubert Decision (1993), and reiterated in their Joiner and Kumho Decisions, in which they addressed the Federal Rules of Evidence (FRE 702), governing Expert Witness Testimony.
The MVQS 2001 Resources (McCroskey, 2001) technical manual contains the technical data, including Statistical Tables with all of the Standard Errors of Measurement, Predictive Validity Coefficients and Standard Errors of Estimates, frequency counts and percentages of jobs at each level of job demand associated with job analysis data profiles in McDOT across all 12,974 specific 9-digit DOT Coded Occupations in McDOT. This technical manual covers the 75 most salient O*NET element variables, the 24 most vocationally salient physical, mental and environmentally significant worker traits, the Vocational Quotient (Job Difficulty Index; Mean=100, SD=15), and the reconstructed 9-point Specific Vocational Preparation (SVP) scale.
5. What methods do you use in collecting, updating and providing the data?
Answer: Typically, as in the past, our methods of data collection and updating the DOT rely primarily on US Department of Labor data available in a variety of forms and cross-walked coded systems. Specifically, McDOT 2003 job requirement profiles were data mined from the 75 most vocationally significant O*NET-98 identified worker trait job requirement element variables for which Means data job requirement profiles were constructed and provided for each of 1,122 Occupational Unit (OU) Classification Code Groups (O*NET OU Codes). This was necessary in order to bridge the gap between the outdated US 4th edition DOT and the updated job demand/worker trait requirement profiles in the McDOT 6th edition DOT.
Since the inception of the McCroskey Series of Job-Person Matching, Transferable Skills, and Earning Capacity Estimation Programs, the programs and their databases have been periodically updated, approximately every two years. In the past, McCroskey Programs have been peer-reviewed in each of three University Comparison Studies of Job-Person Matching Systems (Botterbusch, 1983, 1986 and McDaniel, et. al, 1993). Course Disk 1 was peer-reviewed by Grimley (2000, 2002) in two Journals of Forensic Vocationology, and MVQS 2003 Programs were peer-reviewed, by Streater (2002), in this JOFV Issue.
6. What type of training is available regarding the development and use of MVQS Programs?
Answer: There are four 30-Hour CEU Course Disks specifically designed as graduate-level Distance Education Learning courses for Administrative Law Judges, Vocational Experts, Psychologists, Rehabilitation Counselors, Vocational Evaluators, Social Workers and related professionals. The Course Disk CD- ROMs contain the first 5 Journals of Forensic Vocationology, which serve as text for the 4 Courses. The names of the four Courses are:
• Updating the 5th Edition Dictionary of Occupational Titles. This course covers the history, theory, theory extensions, research and systems leading up to the 1939, 1949, 1965, 1977 and 1991 revised US DOT, and culminates with the development of the McDOT 2001 5th edition DOT.
• MVQS Vocational Analysis. This course covers scientifically-based transferable skills analysis using the MTSP 2003 TSA program which is entirely based on the scientific foundation of the McDOT 6th edition DOT.
• O*NET DOT Database Introduction. This course covers the development of the O*NET-98, the Means data profiles they constructed and the 75 most salient physical, mental and environmental context job requirement elements which were incorporated into the McDOT 5th and now the McDOT 6th Edition DOT and utilized to construct the 24 most vocationally significant worker trait level requirements of each of the 12,775 specific 9-digit DOT coded Occupational Profiles in McDOT 2001 and the 12,974 Occupational Profiles in the McDOT 6.0 DOT. And,
• Vocational Evaluation 001. This course covers the myriad of relevant vocational and mental abilities tests and work samples than are commonly used in vocational analyses by vocational professionals around the US to determine vocational functioning, transferable skills, employability and earning capacity.
7. Can one become certified as reliable in the use of the MVQS 2003 Programs?
In addition to the 4 Training Course Disks, there are 7 sample practicum cases in MVQS 2003. Possession of a valid Masters or Doctoral Degree in Vocationology or a related field of studies (See Page 1 of this Journal for related fields of studies; See also, Vocationologist as defined in McDOT 2003) and two or more years of relevant field experience, along with successful completion of the 4 Course Disks, with 80% or better proficiency on the internal Course Disk Tests, and completion of written reports containing acceptable answers (80% or better proficiency) on the questions posed for each of the 7 sample cases, entitles one to sit for the Certified Rehabilitation Vocationologist (CRV) Exam, which is designed to yield an individualized Inter-Rater Reliability Coefficient Score. All pre-requisites must be met along with an IRR Coefficient score of 0.80 or better to become CRV Board Certified.
8. What's on the foreseeable horizon as far as planned updates for MVQS 2001 Programs?
In response to the need to incorporate the NAICS Codes, which have replaced the SIC Codes, and incorporate the updated SOC Codes, which have replaced the OES Codes in the form of OccCodes and the O*NET OU Codes in the form of O*NET SOC Codes, along with the identification of 199 new jobs in the US Labor Market, we have now completed developing the McDOT 6th Edition DOT & Related Programs slated for release in 2003.
The McDOT 6th Edition DOT has been updated to include the 200 new jobs (i.e., McDOT 6.0 now contains 12,975 specific, fully described, profiled, and cross-walked 9-digit DOT-Coded jobs vs. the 12,775 jobs described, profiled, and cross-walked in the McDOT 5th Edition - Extended Dataset DOT). It includes all the new cross-walk codes and has updated report formats to choose from for screen outputs, editing - using Windows™ Office Links to Word for Windows™ 2000, and/or printing.
The McPLOT 6th Edition TestPlot Program will include approximately 900 tests which can be selected from to build individualized batteries for use in the vocational analysis of individuals. It will continue to have two internal tests, the Occupational Values and Needs Inventory (OVNI) and the Vocational Interest and Personality Reinforcer (VIPR) for interest and personality type assessment relative to job matches. It will have 5 updated report formats to choose from for screen outputs, editing - using Windows™ Office Links to Word for Windows™, and/or printing.
The MTSP 6th Edition TSA Program includes 3,291 Job Bank Databases of known frequently-hired-for jobs: One for each county, parish or borough, in each state in the US, One for each US State, One for each Province in Canada, One for each major city in Puerto Rico, and Job Banks for American Samoa, Guam and the Virgin Islands (St. Croix, St. John and St. Thomas) along with several national-level job banks and one job bank containing all 12,974 specific jobs in the McDOT 6th edition DOT. It has 32 updated report formats to choose from for screen outputs, editing - using Windows™ Office Links to Word for Windows™ 2000, and/or printing. MTSP 6.0 includes a new curvilinear regression earning capacity paradigm, which is more accurate (i.e., with higher predictive validity & smaller Standard Errors of Estimate) than its predecessor. The curvilinear regression earning capacity paradigm was necessary to more closely follow the positively skewed curvilinear line of best fit associated with worker wages in the US economy. (McCroskey, MVQS 2001 Resources Technical Manual, page 92).
The three MVQS 6.0 Edition Programs described above are seamlessly integrated in the Windows™ Access 2000 based platform, which requires a relatively newer and faster computer with approximately 350 megabytes of hard disk space free on an IBM(TM) or IBM compatible PC, with a Windows 95, 98, 2000 ME, or XP based operating system. To insure full installation compatibility on your computer, users need an installed version of MS Office™ 2000 - Professional Edition, which includes Access 2000, prior to installing MVQS 2001 Programs.
MVQS 2003 can also be installed on a Laptop Computer and used for those last minute adjustments, which often have to be made to allow for different hypothetical questions posed by an ALJ, or other interested parties, to Vocational Experts during Expert Witness testimony. The rule of thumb for installing and using MVQS 2003 Programs: the faster the computer, the more efficiently relevant data can be retrieved to answer the myriad of questions which the vocational expert may need to answer with reasonable certainty.
Finally, MVQS 2003 Programs and the MVQS Rehabilitation Economist, which was developed to use Earning Capacity outputs from MTSP 6.0, are empirically based tools, which can efficiently and effectively suggest vocational possibilities and estimates of earning capacity and diminished earning cap city. The programs are wonderful for use in vocational analysis and occupational exploration. However, reserved clinical judgments, made with reasonable vocational and rehabilitation economic certainty, are an absolute necessity if they are to be used effectively in expert witness testimony.
Billy J. McCroskey, Ph.D., Co-Editor, 09/24/02
The McCroskey Vocational Quotient System (MVQS) Theory of Transferable Skills: Revised, Extended and Updated for the 21st Century
By
Billy J. McCroskey, Ph.D., CRE, CRC, CRV, ABVE,
Cynthia P. Grimley, MS, CRC, ABVE,
John M. Williams, D.Ed., ABVE, CRC, NCC, ABDA, CCM,
Steven J. Hahn, MS, CRC, QRC, CRV, CVE,
Jan Lowe, MS, CRC, QRC, ABVE,
William E. Wattenbarger, Ph.D., CRC, CRV,
David B. Stein, Ph.D., CRC, CDMS, LPC, LRC, and
Kenneth L. Dennis, Ph.D., LP, LMFT, CRC, CRV
Abstract
The McCroskey Vocational Quotient System 2001 (MVQS 2001) Transferable Skills Program (MTSP 2001; McCroskey, 2001) provides Transferable Skills Analysis (TSA) based on an equal interval Transferable Skills Percent (TSP) scale. Theoretically, this interval scale ranks job matches in relevant labor markets of interest in terms of suitable employability, from 0 to 97% in terms of Transferable Skills (TS), Occupational Values and Needs Inventory (OVNI), Vocational Interests and Personality Reinforcer (VIPR) Type, Vocational Quotient (VQ), Specific Vocational Preparation (SVP) and Earning Capacity. MVQS TS Theory expands and extends the Minnesota Theory of Work Adjustment [Dawis, England & Lofquist (1964); Dawis, Lofquist & Weiss (1968); Dawis (1976);] with practical applications based on mathematical models underlying a wide variety of vocational databases including the McCroskey Dictionary of Occupational Titles-5th Edition DOT (McDOT 2000/2001; McCroskey: 2000, 2001), the US DOT (US DOL: 1977 & 1991) and O*NET (US DOLETA: 1998) The intent of here is to examine the underlying theory, methodology and rational of MVQS MTSP TSA TSP, its theoretical underpinning and implications for reliable, valid measurement and quantification of MVQS 2001 MTSP TSA TSP Levels, Earning Capacity Estimates and related Analyses.
Introduction
The theoretical model underlying MVQS 2001 Transferable Skills Analysis (TSA) assumes the following key concepts:
1) Work Skills are those skills (knowledge and abilities) acquired by a worker through successfully demonstrated specific vocational preparation (past relevant college, technical, vocational, apprenticeship, and/or on-the-job training) for past, current, and/or future, specific suitable semi-skilled or skilled jobs in the worker's ongoing, evolving career development.
2) Transferable Work Skills are those work skills (knowledge and abilities) acquired through successfully demonstrated specific vocational preparation, required by one or more specific suitable semi-skilled or skilled job matches, to varying degrees of transferability, either in an upward, lateral or downward direction, depending on qualifications (DOQ), in relevant labor markets of interest.[2]&[3]
3) Residual Transferable Work Skills are those work skills (knowledge and abilities) successfully demonstrated through past relevant work history and associated specific vocational preparation, which are retained from past relevant work history based on the clients Residual Employability Evaluative Data Profile, following injury or disability, and required by one or more specific suitable semi-skilled or skilled post-injury or post-disability job matches, to varying degrees of transferability, in one or more relevant geographic labor markets of interest.
The core databases, from which the MVQS 2000/2001 TSA TSP equal interval scale was derived, are included in the McCroskey Dictionary of Occupational Titles 2000/2001 - 5th Edition DOT Updates (McDOT 2000/2001, McCroskey, 2000/2001). McDOT 2000 and McDOT 2001 were updated based on selected transformed O*NET 98[4] DOT replacement worker-trait-element-level data variables (N=75), the United States Dictionary of Occupational Titles-Revised 4th Edition (DOT; US DOL, 1991), post-1991 DOT errata changes and additions and the 28 cluster analysis variables and mathematical models [including outlier reclassification based on Ward's Minimum Variance Method[5] (Ward, 1963)], used to produce the O*NET 98 Occupational Unit (OU) Classification Coded DOT replacement Transferable Skills Groups (N=1,172). Prior to 1998, when the O*NET 98/OU Codes were adopted for use in MVQS MTSP TSA, all earlier MVQS, including the DataMaster, Program series had used GOE[6] codes in place of O*NET 98/OU Codes.
The MVQS 2001 TSA TSP scale expanded the O*NET 98 OU Transferable Skills Groups database DOT replacement TS grouping paradigm (based on 28 grouping variables) to include job-person matching on the 24 most vocationally significant worker traits, along with an identified transferable skills gradient on an overall 5-point equal interval scale across and a 0 to 97% equal interval scale within transferable skills groups.
Literature Review
Decision-making about loss of earning capacity in civil litigation as well as appropriate job placement for persons with or without disabilities for vocational experts, vocational rehabilitation and other vocational counselors has been based, at least in part, on transferable skills analysis (Maze & Williams, 1993; Williams and Maze, 1994). This has been realistic and helpful to understanding and planning during vocational counseling.
The McCroskey Vocational Quotient System (MVQS) TSA TSP Programs have been empirically tested and found to be extremely reliable (3-way inter-rater reliability: Rxxx=0.9864; McCroskey, Haskins & Smolarski, 1995) and valid [i.e., the MVQS TSA TSP 5-point scale was found to be in agreement with 5-point scale ratings from a national sample of Vocational Experts (N=93; Rxy=0.96; SEE=0.357; Grimley, Williams, Hahn & Dennis 2000a, 2000b)]. MVQS TSA TSP information can reliably and validly increase the effectiveness and efficiency of vocational experts and rehabilitation service providers seeking to provide realistic occupational counseling to their clients.
Landsea (1994) pointed out that it is individual-specific factors (e.g. age, education, gender, occupation, industry, and geographical location), which impact the growth of lifetime earnings. This suggests a linkage between acquired knowledge and skills and lifetime earnings. Vocational experts have long viewed transferable skills analysis as a way of determining suitability of specific occupations for a given individual and the impact of occupational choices on earning capacity.
Cutler, Cutler and Ramm (1995) indicated that transferable skills analysis methodologies offered in job-person matching software are commonly used by vocational experts and rehabilitation counselors to identify specific occupations and earnings without any real understanding of the limitations of the data. Cutler, et al opined that using the Dictionary of Occupational Titles (U.S. Department of Labor, 1991) as the basis for identifying the skills and functional capacities associated with jobs was problematic. There were too many problems with the age and aggregate nature of the data.
Cutler, et al (1995) said that frequency of jobs by occupation (as a basis for determining loss of number of jobs to which one may have access pre-/post-injury) was not considered to be entirely accurate. It required too much reliance on aggregate census data. In response, Grimley, et al (2000a, 2000b) reported that Cutler, et al failed to address the fundamental issue regarding validity of the concept of transferable skills by comparing construct validity along with content validity.
In theory and in practice, assessment of transferable skills acquired through work and education has been seen as an effective method for identifying what occupations a worker can perform (assuming their worker trait capacities profile meets or exceeds the job requirement profiles) and what occupations an employer believes an individual has the ability and transferable skills to perform. This forms the basis for suggesting a person can reasonably be successfully placed in a specific job type and can reasonably be expected to earn a reasonable level of income estimated for selected job types in the relevant geographic labor market of interest (Grimley, et al, 2000a, 2000b).
Earlier research involving VDARE[7] profiling of client vocational capacities based on work history requirements, and modified using counselor judgment following a review of written case notes and general medical information, yielded inter-rater reliability estimates as high as Rxxx=0.9944 (McCroskey, 1979, McCroskey & Perkins, 1981). Research comparing counselor produced VDARE Profiles of Client Vocational Capacities with those generated through Rehabilitation Facility Vocational Evaluation results, counselor produced VDARE profiles with placement outcome profiles, facility evaluation produced client profiles with previous facility evaluation results, and facility evaluation produced client capacities profiles with placement outcomes based on VDARE profiles of worker requirements yielded very high validity coefficients ranging from Rxy=0.93 - 0.95 (Burge, 1978; McCroskey, 1979; McCroskey & Perkins, 1981).
Other related research (using job requirements/client capacities comparison profiling) provides additional support for the rationale underlying the MVQS 2001 worker trait factor approach to better understanding individual vocational potential and work history related transferable skills, as a means to improving the quality of basic human services by vocational rehabilitation counselors and evaluators (Colvin, 1972, Field, McCroskey, Grimes & Wattenbarger, 1978; Hanman, 1951; Knowles, 1978; McCroskey, 1979, Reinhardt, 1978; Teal, 1978, Tratner, Fine & Kubis, 1955; Wattenbarger & McCroskey, 1978 and Wattenbarger, 1981.) Most of these articles were cited with research summaries and a full set of references in Chapter 3, Matching People with Jobs: Perspectives on Job Analysis and the Typical Job in the United States (McCroskey & Perkins, 1981, The Manual for the McCroskey Vocational Quotient System, pp 40-56).
Predictive validity of the MVQS MTSP 2000/2001 TSA TSP scale has been empirically tested by comparing the MTSP 2000/2001 TSA TSP rankings with averaged rankings of American Board of Vocational Experts (ABVE, N=93), through the use of the ABVE Transferable Skills Evaluation Test[8]. Specifically, Grimley, et al, (2000a, 2000b) found the MVQS McCroskey Transferable Skills Program (MTSP 2000/2001) Transferable Skills Percent scale to be a valid predictor of averaged Vocational Expert responses on the ABVE Transferable Skills Evaluation Test (TSET; McCroskey & Dennis, 2000).
The ABVE TSET instrument was developed based on the MTSP 2000/2001 TSA algorithm. It incorporated O*NET 98 Transferable Skills groups and a series of related job analysis codes to create and stratify transferable skills on a per cent scale ranging from 0 to 97% across, and within, the updated O*Net 98 Transferable Skills Groupings.
In Grimley, et al, (2000a, 2000b), the ABVE TSET was subdivided into five broadly defined ascending Transferable Skills Levels ranging from 1 to 5 across the TSP 0 to 97% continuum, and administered to 93 Vocational Experts at the ABVE 2000 Spring Conference in New Orleans, LA. The Predictive Validity Coefficient between the MTSP 2000 TSP rankings and the criterion-referenced Prediction Estimates of the Vocational Experts (N=93) was extremely high (Rxy=0.96). Correspondingly, the Coefficient Of Determination (R2=0.92) was extremely high, and the Standard Error of Estimate (SEE=0.357) was found to be well within reason.
The Outdated Transferable Work Skills Definition
Williams (1998) stated that computer programs based on DOT (1991) ran the risk of not controlling for methodological error variance if not basing the sorting functions of the software on the appropriate factors. He went on to explain that the Revised Handbook for Analyzing Jobs (HAJ-R, 1991) listed three variables that were relevant to assessment of transferable skills: Work Fields, MPSMS and Specific Vocational Preparation (SVP).
1. Work Fields are Machine, Tools, Equipment and Work Aids (MTEWA) grouping codes that reflect how work gets done, the result of work, and the purpose of the job. Although these categories range from specific to general, they represent homogeneous groups related to technologies or objectives. It is easy to justify the inclusion of Work Fields into a Transferable Skills Analysis. People can acquire skills in getting work done, and these skills can be transferred to another job.
2. Materials, Products, Subject Matter, and Services (MPSMS) grouping codes describe what a worker does and what gets done to what. This coding structure is similar to the Work Fields structure, and its use in Transferable Skills Analysis appears logical. Skills related to what the worker does and how this work is completed can realistically be transferred to another job.
3. Specific Vocational Preparation (SVP) is the amount of lapsed time required for a typical worker to learn the techniques, acquire the information, and develop the facility needed for average performance in a specific job-worker situation. Use of SVP as a selection variable in Transferability of Skills Analysis (TSA) assumes that the individual can perform all occupations, which have the same or lower SVP, and that jobs requiring an SVP of no more than 2 (up to 1 month), are unskilled jobs. Since SVP represents time required to learn a job (though on-the-job training, formal vocational or academic training) and not any inherent knowledge or skill associated with the job, SVP cannot be transferred from job to job; instead, it is used primarily in differentiating between unskilled jobs (with an SVP level of either 1 or 2) and semi-skilled or skilled jobs. However, SVP is highly correlated with Overall Job Difficulty as measured by the McCroskey Vocational Quotient (VQ), Reasoning (R), Math (M) and Language (L) Development, that can be identified in terms of individual capacities and job requirements. Therefore, these factors may be more predictive of ability to perform specific job tasks than SVP alone. Use of SVP as a discriminator of what jobs are screened out during a TSA may not make sense when VQ, R, M and L development are not considered. This is particularly true when injured persons are limited by physical or mental impairments to sedentary or light work where the preponderance of jobs requires higher SVP levels than many medium or higher exertion level occupations. SVP alone may be overly exclusive. However, SVP may have significant value in determining those jobs which are more likely to be available to a given individual based on employer perception of minimum demonstrated knowledge and/or skills required for being hired. This is a different issue than transferable skills, but an important part of any earning capacity analysis.
Prior to the vastly improved O*Net Transferable Work Skills Groupings coupled with the MVQS TSA TSP scale replacement data, the outdated SSA Transferable Work Skills Definition stated in the Code of Federal Regulations (20CFR404.1568, 383-385), as it related to Social Security Disability Insurance (SSDI) eligibility decision-making, was generally accepted as the fundamental basis for most transferable skills analyses. Restated for clarity, it said:
1) What we mean by transferable skills. We consider you to have skills that can be used in other jobs, when the skilled or semi-skilled work activities you did in past work can be used to meet the requirements of skilled or semi-skilled work activities of other jobs or kinds of work. This depends largely on the similarity of occupationally significant work activities among different jobs.
2) How we determine skills that can be transferred to other jobs. Transferability is most probable and meaningful among jobs in which--
• The same or a lesser degree of skill is required;
• The same or similar tools and machines are used; and
• The same or similar raw materials, products, processes, or services are involved.
3) Degrees of transferability. There are degrees of transferability of skills ranging from very close similarities to remote and incidental similarities among jobs. A complete similarity of all three factors is not necessary for transferability. However, when skills are so specialized or have been acquired in such an isolated vocational setting (like many jobs in mining, agriculture, or fishing) that they are not readily usable in other industries, jobs, and work settings, we consider that they are not transferable.
4) Transferability of skills for individuals of advanced age. If you are of advanced age (age 55 or older), and you have a severe impairment(s) that limits you to sedentary or light work, we will find that you cannot make an adjustment to other work unless you have skills that you can transfer to other skilled or semiskilled work (or you have recently completed education which provides for direct entry into skilled work) that you can do despite your impairment(s). We will decide if you have transferable skills as follows. If you are of advanced age and you have a severe impairment(s) that limits you to no more than sedentary work, we will find that you have skills that are transferable to skilled or semiskilled sedentary work only if the sedentary work is so similar to your previous work that you would need to make very little, if any, vocational adjustment in terms of tools, work processes, work settings, or the industry. (See Sec. 404.1567(a) and Sec. 201.00(f) of appendix 2.) If you are of advanced age but have not attained age 60, and you have a severe impairment(s) that limits you to no more than light work, we will apply the rules in paragraphs (d)(1) through (d)(3) of this section to decide if you have skills that are transferable to skilled or semiskilled light work (see Sec. 404.1567(b)). If you are closely approaching retirement age (age 60-64) and you have a severe impairment(s) that limits you to no more than light work, we will find that you have skills that are transferable to skilled or semiskilled light work only if the light work is so similar to your previous work that you would need to make very little, if any, vocational adjustment in terms of tools, work processes, work settings, or the industry. (20CFR404.1568, 383-385)
Updating the Outdated Transferable Skills Definition
Specific Vocational Preparation (SVP) is by definition on an ordinal (rank ordered) scale of measurement which is highly correlated with overall job difficulty as measured by the interval scale Vocational Quotient (VQ; McCroskey, 1981). Inclusion and use of more appropriate equal-interval-scale variables, like the VQ, as an index of overall job difficulty/work capacity, along with MVQS TSA TSP equal-interval-scale data, helps overcome SVP ordinal scale limitations, and has strongly impacted conventional thinking of many experts in our field about the theory and practice of Transferable Skills Analysis.
The McCroskey Transferable Skills Program (MTSP 2001) uses the Vocational Quotient (VQ) to define vocationally significant worker trait job demands/requirements and corresponding worker capacities. The VQ weights the complexity and difficulty of Job Types based on their profiles of job demands, providing an appropriate control on academic, intellectual, attending, physical capacity, environmental tolerance and related worker trait job demands/requirements and people worker trait capacities covered under the four most vocationally significant worker trait factors and their 24 most vocationally significant worker traits.
Primary Considerations should first be given to the 24, Most Vocationally Significant MVQS VQ Variables, before any other Transferable Skills Indicator Variables are considered
The Worker's Four-Factor by 24 most vocationally significant MVQS Worker Trait Level Evaluative Data Capacities Profile must match or exceed the updated McDOT 2001 5th ed. DOT Job Demands Profile relative to any given jobs before Transferable Skills should be considered relative to a worker's past relevant work history. These include:
1. General Educational Development (GED) / Intellectual Functioning
• (R) - Reasoning Development; Replaces (G) - General Intellectual Aptitude, which was inappropriately truncated at the low end.
• (M) - Math Development; Replaces (N) - Numerical Aptitude, and
• (L) - Language Development; Replaced (V) - Verbal Aptitude;
2. Aptitudes
• Perception
• (S) - Spatial Perception,
• (P) - Form Perception, and
• (Q) - Clerical Perception,
• Dexterity
• (K) - Motor Coordination/Bimanual dexterity Aptitude,
• (F) - Finger Dexterity Aptitude, and
• (M) - Manual Dexterity,
• Other
• (E) - Eye-Hand-Foot Coordination, and
• (C) - Color Discrimination;
3. Physical Demands
• (PD1) - Lift, carry, push, pull, sit, stand, walk,
• (PD2) - Climbing, balancing,
• (PD3) - Bend, stoop, crouch, squat, kneel, crawl,
• (PD4) - Reaching, handling, fingering, feeling,
• (PD5) - Talking, hearing, writing,
• (PD6) - See up-close and see far-away; and,
4. Environmental Tolerances
• (EC1) - Work location
• (EC2) - Extreme cold,
• (EC3) - Extreme Heat,
• (EC4) - Dampness, wetness, humidity,
• (EC5) - Noise, vibrations,
• (EC6) - Hazards: machinery, electrical, chemical, unprotected heights, and
• (EC7) - Adverse Atmosphere: dusts, fumes, odors, mists or gases.
VQ Research: Implications for Transferable Skills Analysis
VQ has been frequently validated (and cross-validated) as a reliable, valid and very high predictor of Wages Offered on Job Service Work Orders as well as Workers (McCroskey & Hahn, 1997; Mayer, 1998). VQ has also been found to be a reliable, valid, and a very high predictor of earning capacity, as measured by reported Occupational Employment Statistics (OES) income data at the Mean as well as at the 10th, 25th, 50th (Median), 75th and 90th Percentile Wage Distributions (McCroskey, Hahn & Dennis, 2000).
The VQ (and all the scientific research data underpinning it) combined with SVP and related considerations shores up the testimony of Vocational Experts. This combination shores up their testimony foundation with much more defendable scientifically underpinned explanations for TSA and Earning Capacity predictions along with known error rates. For example, knowing that SVP has been established to have very high predictive validity along with known very low error rates (Rxy=0.90, SEM=0.02, SEE=0.92, McCroskey, 2001[9]) and that VQ has been established to have even higher predictive validity along with known very low error rates (Rxy=0.97, SEM=0.13, SEE=3.81), it would be much easier to defend a job match with an SVP of 1 or 2, which also has a VQ of 84 or less (in the below average job difficulty range at less than the 16th percentile of overall job difficulty), as being unskilled, than a job with an SVP of 1 or 2 and a VQ of 100 (the 50th percentile of Overall Job Difficulty in the United States). In MVQS Transferable Skills Analysis, this is a major consideration.
The O*NET Viewer and Transferable Skills Analysis
The O*NET Viewer contained its own, very crudely defined, transferable skills analysis module (Related Occupations Module Option), which did not represent actual occupations (Dennis & McCroskey, 1999). Instead, it represents fairly large groupings of possibly related (and often unrelated) O*NET OU coded groups of jobs. Suitably related jobs can be found in the O*NET data, but the information provided in the Related Occupations module can only be used in the most general terms. For example, the OU code of 34002E is Managing Editors. Related Occupations listed Book Editors (34002G), Program Directors (34056H), Audiovisual Specialists (31508), Producers (31511C), Technical Writers (34005), and Museum Research Workers (31511C).
The connection between some of the above-listed OU cluster analysis groupings is fairly clear. However, it also listed (as part of its up to 10 groupings) Employee Relations Specialist (21511C) as being related. It can be seen that the OU code changed from starting with a 3, to starting with a 2. It would be hard to explain how the skills could be easily transferred. Other occupations included were First Line Supervisors, Administrative Support (51002B) and Appraisers, Real Estate (43011). Except for getting people to draw pictures of houses for the newspaper, it is difficult to understand what skills would transfer from a Managing Editor to a Real Estate Appraiser.
O*NET 98 transferable skills groups were created based on cluster analyses by mathematically grouping jobs that had similar requirements on 28 variables, and excluding other job groupings that were not similar enough based on these 28 variables.
The O*NET 98 Transferability Of Skills Grouping Paradigm[10]
The Job Analysis Variables (N=28) selected and used by O*NET 98 in their cluster analyses and development of Transferable Skills Groups (N=1,172) included:
1) Primary Materials, Products, Subject Matter and Services (MPSMS) code,
2) Secondary Materials, Products, Subject Matter and Services (MPSMS) code,
3) Tertiary Materials, Products, Subject Matter and Services (MPSMS) code,
4) Primary Work Field: Machines, Tools, Equipment and Work Aids (MTEWA) code,
5) Secondary Work Field: Machines, Tools, Equipment and Work Aids (MTEWA) code,
6) Tertiary Work Field: Machines, Tools, Equipment and Work Aids (MTEWA) code,
7) Specific Vocational Preparation (SVP),
8) (D)ata Complexity,
9) (P)eople Complexity,
10) (T)hings Complexity,
11) General Educational Development: (R)easoning,
12) General Educational Development: (M)athematical,
13) General Educational Development: (L)anguage,
14) (G)eneral Learning Ability Aptitude,
15) (V)erbal Aptitude,
16) (N)umerical Aptitude,
17) (S)patial Perception Aptitude,
18) (P) Form Perception Aptitude,
19) (Q) Clerical Perception Aptitude,
20) (K) Motor Coordination Aptitude,
21) (F)inger Dexterity Aptitude,
22) (M)anual Dexterity Aptitude,
23) (E)ye-Hand-Foot Coordination Aptitude
24) (C)olor Discrimination Aptitude
25) (D)irecting Temperament,
26) (P)eople Temperament,
27) (I)nfluencing Temperament, and
28) (E)xpressing Temperament.
O*NET 98 originally grouped 12,761 DOT occupations into 852 Occupational Employment Statistics (OES) occupations. This number was considered too small, and statistical clustering was employed to divide the OES codes into sub-categories. Ultimately, this resulted in 1,122 rated and viewable OU groupings that were considered to have more homogeneous skills that represented meaningful differences between occupations. The OU groupings were structured to display Belongingness (matching occupational definitions) and Homogeneity (more similar skills within groups than between groups) for the purpose of determining skill transferability.
As a result of the Cluster Analyses which were completed and finalized for the new O*NET 98 Transferable Skills Groupings, 1,172 Occupational Unit Classification (OUC) Groups, or, as they have become better known, O*NET Code Transferable Skills (TS) Groups were created.
O*NET Code TS Groups were based on USDOL Occupational Employment Statistics (OES) Code Groups, which were identified by the first 5 digits, of each 5-digit or 6-character O*NET 98 Code TS Group. Thus, OU Classification/O*NET 98 Coded TS Groups were more highly refined, empirically derived, Transferable Skills (TS) Subgroups, within the OES Code Group Classification Structure.
Of the 1,172 identified O*NET 98 Coded TS Groups, Means Data Profiles on 483 worker trait elements for 1,122 groups were reported in the US DOLETA O*NET 98 Version 1.0 Program. Researchers at Vocationology, Inc. constructed Means Data Profiles with 483 worker trait elements for the remaining 50 O*NET 98 Coded Groups (not reported in the O*NET 98 Vers. 1.0 Program) and added two new groups (each containing only 1 job), bringing the total N to 1,174 TS groups. Vocationology researchers also reconstituted 12 jobs which were reclassified with different 9-digit DOT Codes by O*NET 98 researchers.
In the O*NET 98 Version 1.0 Viewer Program, there were 1,122 OU TS Groups for which means data element profiles were viewable in the O*NET 98 Viewer. There were 12,761 9-digit DOT-Coded Job Types contained in the O*NET 98 DOT Crosswalk of unduplicated jobs, and 12,797, 9-digit DOT-Coded Jobs contained in the O*NET 98 DOT Crosswalk when duplicated jobs are included. No specific job analysis worker trait profiles were included for any job types listed in any of the O*NET 98 databases.
In the McDOT 2000/2001 programs, there are 12,775 specific unduplicated 9-digit DOT-Coded Jobs and 12,811, 9-digit DOT-Coded Job Types contained in the McDOT 2000/2001 Crosswalk when duplicated jobs are included. In McDOT 2001, each job has a specific worker traits/job requirements profile, with respect to the 24 most vocationally significant worker traits and 3 aggregate variables (VQ, SVP and ZONE).
Many O*NET 98 OU codes were either too broad, or too narrow (on their own), to use as stand-alone transferable skills groups. However, coupling together the 1,172 O*NET 98 database Occupational Unit (OU) transferable skills groups with the MVQS TSA TSP scale, as major components of the MVQS MTSP 2000/2001 transferable skills analysis algorithm, significantly improved the TSA TSP capabilities of the MVQS McCroskey Transferable Skills Programs (MTSP 2000/2001; McCroskey, 2000, 2001), in terms of distinguishing occupations most reasonably related via true transferability of skills.
Face, Content and Construct Validity became much more apparent in the MTSP 2001 program than in the stand-alone O*NET 98 OU code groups themselves. The clarity of the MVQS MTSP transferable skills algorithm allowed the MTSP transferability scale to be converted from its previous 1 to 46 level Raw Score Scale to its 5-point standardized interval scale, Transferability of Skills Percent (TSP; 0-97%)scale. MTSP 2001 users have found the percentage based TSP rated outputs for MTSP Job Matches much more intuitive, understandable, easier to interpret, easier to defend and easier to explain.
TSA software programs are now faced with the challenge of integrating O*NET data with traditional DOT data to predict actual jobs an individual can perform and the level of expected earnings associated with these selected occupations. Traditional thinking about TSA improvements offered via use of the Vocational Quotient (VQ; Williams, 1998; McCroskey and Hahn 1997; 1998a; 1998b) and the 24 most vocationally significant worker trait requirements from which it is constructed, must lead vocational experts and counselors to ask the less technical and possibly more initially critical questions of whether or not the construct of transferable skills has been sufficiently understood and explained to the professional community and whether or not sufficient consensus on what this construct means and how it should be used in TSA software has been developed.
Without construct validity, TSA software will have little value to predict suitable jobs and associated earnings. To the end of determining if transferable skill is a meaningful construct that can be used reliably to predict suitable occupations for individuals (i.e., predictive validity), the Grimley, et al (2000a, 2000b) was a meaningful first step. In that study, it was hypothesized that if Vocational Expert opinion and the TSA TSP results of MVQS MTSP 2000/2001 software were shown to be consistent, one could argue the concurrent validity of the software and vocational expert opinion. To that end, the Grimley, et al, study assessed the concurrent validity between vocational expert opinions and the results of the McCroskey Transferable Skills Program (MTSP 2000/2001).
Specifically, in the Grimley, et al, study, the McCroskey Transferable Skills Program (MTSP 2000/2001) Transferable Skills Percent (TSP) scale was found to be a valid predictor of the averaged responses of 93 Vocational Experts tested using the ABVE Transferable Skills Evaluation Test instrument. The Predictive Validity Coefficient between the MTSP 2000/2001 TSP rankings and the criterion-referenced Prediction Estimates of the Vocational Experts (N=93) was extremely high (Rxy = 0.96). Correspondingly, the Coefficient Of Determination (R2 = 0.92) was extremely high. Finally, the Standard Error of Estimate (SEE = 0.357) was found to be very reasonable. In essence, the Grimley, et al, study found strong support for concurrent, predictive, and underlying construct validity of the McCroskey Vocational Quotient System (MVQS) Theory of Transferable Skills and the resulting MTSP TSA TSP algorithm embodied in the MTSP 2000 and 2001 Programs.
The MVQS Transferable Skills Algorithm
MTSP 2001 first looks at VQ and then matches people with jobs on the 24 most vocationally significant worker trait variables. Job-person matches with VQs of 85 or greater (the semi-skilled to skilled work range), which match the worker's evaluative data profile relative to profiles of job demands (in the geographically selected MTSP 2001 job bank database of choice) on the 24 most vocationally significant variables extracted from McDOT 2001 are first considered for potential TS level assignment during the MTSP 2001 TSA process. Job-person matches with VQs less than 85 are assumed to be unskilled jobs and are therefore considered last during MTSP 2001 TSA process.
The MVQS McCroskey Transferable Skills Program (MTSP, McCroskey, 2000; 2001) use a combination model to produce the TSA Transferable Skills Percent (TSP) values for each job-person evaluative data profile match relative to similarities between selected cross-walks associated with job person matches and successfully demonstrated past relevant client work history. Numerical TSA TSP values are accumulated in the MTSP 2001 Program to produce a theoretical representation of the relative percent of total skills that are transferable from past relevant work history to each identified job-person match.
Following comparison on the O*NET Occupational Unit Classification (OUC) Code which produces a similar comparison on 28 vocational variables, the TSP Scale is incorporated to produce a much more refined TSA Scale Ranking. Briefly, an overview of the MTSP TSA TSP Scale Rankings Algorithm is described below.
The MVQS MTSP TSA TSP Algorithm Overview
TSP Level TSP Range Verbal Scale
Level 5 80 - 97% = semi-skilled or skilled job(s) with high transferable skills
Level 4 60 - 79% = semi-skilled or skilled job(s) with moderate transferable skills
Level 3 40 - 59% = semi-skilled or skilled job(s) with low transferable skills
Level 2 20 - 39% = semi-skilled or skilled job(s) with few if any transferable skills
Level 1 0 - 19% = unskilled job(s) with no significant transferable skills
The Highest MVQS Transferable Skills Percent (TSP) Level
Jobs in the highest overall level of Transferable Skills (TS) fall in the 80 to 97 percent TS range. These TS levels are reached when a worker returns to a past relevant work history job, or a job-person match with the same (or highly similar) DOT Code (first 3 digits must match exactly), OU Classification/O*Net Code (all 5 or 6 characters must match exactly) and Work Duties. Job-person matches at the highest TS level (97%)[11] must also exactly match work history on six TS relevant Crosswalk Codes, (i.e., SIC, SOC, CEN, IND, MPSMS & Work Field/MTEWA codes) to achieve a TS level of 97%.
The Semi-Skilled to Skilled Work Range
For each job-person match with a VQ of 85 or greater (the 16th to 99th+ Percentile range), MTSP 2001 assumes the job match to be in the semi-skilled to skilled work range and evaluates the cumulative number of all possible crosswalk code matches between the person's identified work history set of jobs relative to each individually identified job-person match. Following this, the Transferable Skills Percent (TSP) algorithm accumulates a two-digit TS value. The first digit (tens value) of each TS value represents job match similarities between work history and job-person matches on the DOT and O*NET coding systems.
The Lowest MVQS Transferable Skills Percent (TSP) Level
If a job-person match has a Vocational Quotient (VQ) less than 85, that job is considered unskilled and the MTSP 2001 TSA Transferable Skills Percent level is automatically restricted to the 0 to 19 % unskilled TS range, depending on the number of crosswalk code matches for that job relative to the client's past relevant work history.
In the Grimley et al, study, the verbal rating levels (from highest to lowest possible TSA level) were attributed to the objective MTSP TSA TSP rankings, and they matched the 5-point overall ranking scale on the ABVE Transferable Skills Evaluation Test instrument. This scale was derived directly from and based specifically on the MVQS MTSP TSP algorithm.
The total MTSP TSA TSP TS value (Range = 0 to 46) was mathematically transformed to produce a total percent of all available TSP TS scale points (Range = 0 to 97%). This transformation does not exceed a total possible percent of 97. Theoretically, this top level represents the theoretical assumption that no two job-worker situations are 100 percent identical, but that they may approach such unity. MTSP 2001 TSP TS Levels are transformed to a percent based scale based on 65 comparison variables.
• Variable 1: Relative to VQ, only those job person matches with a VQ of 85 or greater are considered relevant for TS analysis relative to the five-point, 0-97 Percent, MVQS 2001 TS analysis scale:
1. No Significant TS Rating (0-19 Percent TS Range). Job-person matches with a VQ of less than 85 are assumed to fall in the unskilled work range and automatically receive the lowest possible TS Range Rating.
2. Few, If Any, TS Rating (20-39 Percent TS Range),
3. Low TS Rating (40-59 Percent TS Range)
4. Moderate TS Rating (60-79 Percent TS Range) or
5. High TS Rating (80-97 Percent TS Range).
• Variables 2-25: Relative to the 24 McDOT 2001 most vocationally significant job-person matching variables, all 24 values in the person's evaluative data profile must equal, or exceed, the 24 corresponding values in the job demands profile, before any job-person matches can occur in a specific geographic job bank database and be considered for a TS level assignment based on the degree of similarity between job-person matches and jobs in past relevant work history.
• Variables 26-28: Relative to the 9-digit McDOT DOT Code, three codes are considered incrementally in sets:
1. The 1st McDOT Code digit, or DOT Occupational Category,
2. The 1st two McDOT Code digits, or DOT Occupational Division, and
3. The 1st three McDOT Code digits, or DOT Occupational Group.
• Variables 29-31: Relative to the 5 or 6 digit OU Classification/O*Net Code, three codes are considered incrementally in sets:
1. The 1st two digits of the OU Classification/O*Net Code,
2. The 1st four digits of the OU Classification/O*Net Code, and
3. All 5 or 6 digits of the OU Classification/O*Net Code).
• Variables 32-59: The 28 O*NET TS grouping variables at the tens level, and
• Variables 60-65: The 6 vocational crosswalk database codes at the ones or units level (i.e., SIC, SOC, CEN, IND, MPSMS and Work Field/MTEWA Codes).
MTSP 2001 TSA TSP Scale: High, Moderate & Low TS Levels
MTSP 2001 TSA TSP High, Moderate & Low Level TS points accumulate as follows:
The First Digit (Tens Value)
• The highest TSP levels (80 - 97%) require the target job to match the reference job on the first 3 digits of the McDOT 2000/2001 code and all 5 or 6 of the O*NET code.
• The next TSP level (60 - 79%), the two jobs must match either the first 3 digits of the McDOT 2000 code or all 5 or 6 digits of the O*NET code. Or, match the first 2 digits on the McDOT 2000/2001 code and the first 4 digits of the O*NET code.
• To acquire the third level of TSP (40 - 59%), the jobs must match either the first 2 digits of the McDOT 2000/2001 code or the first 4 digits of the O*NET code. Or, match the first digit of McDOT 2000/2001 code and the first 2 digits of the O*NET code.
The Second Digit (Ones or Units Value)
The second digit (ones value) is of the Transferable Skills (TS) value for each job match is a direct accumulation for matching on primary codes from six crosswalk code databases. This digit is incremented for each match of the two jobs on the following primary crosswalk codes:
• Standard Industrial Classification (SIC) Code
• Standard Occupational Classification (SOC) Code
• Census (CEN) Code
• Materials, Product, Subject Matter and Services (MPSMS) Code
• Work Field (MTEWA) Code
• Industry (IND) Code
Discussion, Conclusions and Recommendations
Research results cited in this article support very high Reliability, along with, very high Face, Content, Construct, Predictive and Concurrent Validity for the MVQS MTSP Transferability Skills Percent (TSP) Algorithm in the McCroskey Transferable Skills Programs (MTSP 2000 & 2001). Professional consensus about what the construct of transferability of skills entails and methodological consensus between experts and software about TSA results has been found and reported in peer-reviewed research[12].
Dennis and Dennis (1998) asked if any TSA software would stand the scrutiny of the Daubert standard for admissibility of expert testimony in federal court. Collaterally they asked if any TSA software, with its strengths and limitations, was a valuable tool for making decisions about jobs and earning capacity in life and in courtrooms. They found MVQS 2000/2001 programs to fit the bill. If TSA software methodologies are to meet the standard of science that is possible (given that the behavioral sciences typically lack the inherent control of error variance found in the natural sciences) and are to be recognized as a valid predictors of realistic job options and earning capacity for persons with or without disabilities, more research on the validity of TSA methodologies needs to occur.
In the Grimley et al, study, 92% of the variance in TSA Expert Responses was controlled or accounted for by the MVQS MTSP TSA TSP Algorithm. Vocational Expert consensus has been reached about the theoretical constructs and the standardized MVQS MTSP TSP algorithm embodied within the MTSP 2000 & 2001 TSA programs. In a nutshell, that study empirically demonstrated that the opinions of vocational experts agree with and are highly reflected in the parameters and outcomes embodied in the MTSP 2000/2001 TSA TSP theory and methodology. Those findings clearly cross-validate and enhance the credibility of clinical judgments made by vocational experts employing MTSP TSA TSP theory and methodology in terms of assisting a Trier of Facts, an individual or other interested parties, as they seek to make sound decisions regarding employability and earnings capacity based on objective, reliable and accurate Transferable Skills Analyses.
Transferable skills (TS) are acquired through Specific Vocational Preparation Training as well as On-The-Job Training during on-going successful Job Tenure. Thirty years ago, the Minnesota Theory of Work Adjustment (MTWA) provided an excellent model for Job-Person Matching leading to reasonable expectations of Job Satisfaction and successful Job Tenure. It seems to have stopped there and needs to be revised, extended and updated for the 21st Century.
The Minnesota Theory of Work Adjustment should be revised, extended and updated to allow it to be viewed from the perspective of an on-going, reiterative, career development process, leading from one job to the next over time during normal individual career development, for it to adequately account for Transferable Skills Building and Transferable Skills Analysis, and Earning Capacity Estimation. This article presents strong support that theoretical expansion of the MTWA should be based on the content and implications of this article, which reflect what has already been theoretically developed, programmed, successfully demonstrated in the MVQS 2001 MTSP TSA TSP approach to Transferable Skills Analysis and Earning Capacity Estimation. This approach has been shown through scientific research to be leading edge technology in terms of job-person matching, transferable skills analysis and earning capacity estimation. It has also been shown through numerous scientific research articles to be highly reliable and highly valid with very reasonable, relatively low error rates (See References and Bibliography).
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The MVQS[13] Vocational Interest and Personality Reinforcer (VIPR) Job-based Vocational Personality Type Indicator and MTSP[14] Jobs-Based Vocational Interest Personality Types Crosswalk to Jung People-Based Personality Types
By
Billy J. McCroskey, Ph.D., Steven J. Hahn, M.S.,
Scott E. Streater, D.V.S., Larry L. Sinsabaugh, Ph.D.,
Lyndette L. Mayer, Ph.D., Eugene E. Van de Bittner, Ph.D.,
Janet K. Lowe, M.S. and Kenneth L. Dennis, Ph.D.
Abstract
According to Personality Theorist Carl Jung[15], human motivation to act or behave in predictable ways may be explained in terms of creative energy and classified into a variety of Jung People-based Personality Types based on different combinations of four dimensions of opposing personality trait continuums:
• Extravert vs. Introvert,
• Sensing vs. iNtuiting,
• Thinking vs. Feeling, and
• Judgment vs. Perception.
Combining opposing personality dimensions by selecting one end of each of the four continuums (E or I, and S or N, and T or F and J or P) yields 16 four-letter MVQS Vocational Interest and Personality Reinforcer (VIPR) Job-based Personality Types[16]. Each of these have a corresponding Jung People-based Personality Types (e.g., ESTJ, ISTJ, ENTJ, INTJ, . . . ENFP, INFP). The 16 VIPR Job-based Personality Types can be helpful in terms of describing and explaining vocational aspects of complex human behavior. They can also be helpful in matching individuals with Specific Job Types, via the MVQS2001 VIPR Job-based Personality Type Crosswalk, which optimally reinforce (correspond with) their Vocational Interests, Occupational Values, Needs, and General Jung People-based Personality Type.
© 2001 by Billy J. McCroskey, Ph.D.
All Rights Reserved.
Filename: C:\My Documents\VIPRART.doc
Purpose of the Study
The purpose of this study was:
1) To reasonably order the 12,775 Specific Job Types described in the McDOT2001 into 16 General Vocational Interest and Personality Reinforcement (VIPR) Job-based Personality Types. These General Job-based Personality Types would include seemingly Independent, yet Dependent, Specific Job Types, within and across, the 16 General VIPR Job-based Personality Types, when ordered by Percent of Transferable Skills Valence[17] across all 12,775 Specific Job Types.
• Note: Retaining Specific Job Types with the highest TS Valence in each single best General VIPR Job-based Personality Type, and eliminating all other duplicate, or lower TS Valence Specific Job Types, within and across, the 16 General VIPR Job-based Personality Types, brings more independent order to the world of work. By forging a link between General Jung People-based Personality Types and their single-best most correspondent General VIPR Job-based Personality Types, we can better match people with jobs based on relevant Personality attributes. The 16 corresponding Job-Person Personality-based Job-Person Matching Types were developed so Career Guidance and Counseling Professionals could provide Personality-based career guidance and counseling to their clientele. How so? By considering which General Jung People-based Personality Type best fits which General VIPR Job-based Personality Type as defined by the set of Specific Job Types nested within each VIPR Job-based Personality Type.
2) To develop an MVQS Vocational Interests & Personality (VIPR) Job-based Personality Type Indicator (both a Paper and Pencil, and a Machine version) which classifies all 12,775 Specific McDOT2001 Job Types into 16 General VIPR Job-based Personality Types, corresponding with the 16 General Jung People-based Personality Character Types[18] identified in the literature.
Review of Literature
The Origins of Job-Person Matching
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In the early 1930s, the United States Department of Labor (US DOL) began widespread studies of the requirements of jobs in America. These studies were initially prompted by the need to understand job requirements to better match disabled veterans with jobs. The goal was to reduce or eliminate the impact of vocationally handicapping conditions (McCroskey, 1979; McCroskey & Lowe, 1986, 1987; McCroskey, Streater, Timming, Wattenbarger & Lowe, 1989, 1991).
In 1933, the United States War Manpower Commission received congressionally-authorized funding for job analysis research, which later produced the first edition of the Dictionary of Occupational Titles (DOT, US DOL, 1939). That book was an attempt to objectively describe all jobs in the United States. Eventually, the US DOT served as a model copied by many countries around the world [(McCroskey & Lowe, 1986, 1987); Shartle (1964)]. Subsequent editions of the DOT, Volumes II, III and IV, were researched using objective, behaviorally-anchored Job Analysis Scales and Techniques, described, quantified and published in 1949, 1965, and 1977, respectively.
In 1991, instead of researching and updating to a 5th edition DOT, the 1977 4th edition DOT was simply revised and became known as the 1991 revised 4th edition DOT.
In 1998, the O*NET 98 Viewer (Version 1.0) was put out, not as an updated DOT, but as a replacement for the DOT. It contained far too much general information and not nearly enough specific to be of much use to Vocational Experts, Career Guidance Counselors, Vocational Rehabilitation Counselors or Consultants, Vocational Evaluators, Psychologists, Psychometrists, or similar professionals.
In 2000, since the USDOL had abandoned updating US DOT to a 5th edition, the McCroskey Dictionary of Occupational Titles (McDOT) was updated to a 5th Edition DOT by Vocationology, Inc., a private sector firm in Brooklyn Park, MN. The methods used included a great deal of data mining of the O*NET 98 DOT replacement data along with the data fusion necessary to rebuild the 24 most vocationally significant worker trait profiles for the 12,775 Specific Job Types in McDOT2001.
The Jung Connection to VIPR Type Indicators
The VIPR code was determined from Jung, C.G. (1971). Myers-Briggs resources from Consulting Psychologist Press (CPP) were noted, but not used. We went back to the original source (Jung, 1971). The VIPR types are numbered in order of frequency in the McDOT. Number 1 is the most common type and number 16 is the least common type. While a person may have a personality type (or Conceptual Type as we would describe it), the desired VIPR type is specific to employment. VIPR does not say what type you are. It says what type of job you prefer to have. For many people, personality type is the same as the employment preference type. This cannot be assumed, however, for all workers. Since the VIPR test asks the person to rate jobs on the basis of desirability, it focuses on work preference rather than general personality. Therefore, in its development, focus and prediction, VIPR is not related to Myers-Briggs. Carl Jung remains the theoretical base for the 16 VIPR Type Indicators.
Evaluative Data Profiling
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The 24 Most Vocationally Significant Worker Traits for Manual and Computerized Job-Person Matching
Since the introduction of the formal Minnesota Theory of Work Adjustment in 1964, the US DOL has collected a myriad of worker trait / job requirement element-level data, and utilized that data to develop worker trait / job requirement traits-level data.
McCroskey (1982,1983, 1985, 1987, 1989 & 1990) and McCroskey & Lowe (1986, 1987) described the 24, most vocationally significant, traits-level worker traits, which should be measured, or rated, and used for evaluative data profiling in McCroskey Vocational Analysis. This 24 worker traits-level characteristics evaluative data profile should be developed using the McPLOT TestPlot Program and then transferred to the McCroskey Transferable Skills Program (MTSP; McCroskey, 2000) for the best, most reliable and most well validated Job-Person Matching, Employability Determination, and Earning Capacity Prediction Estimates. All of these worker traits have been operationally defined on behaviorally anchored job analysis scales in the Handbook for Analyzing Jobs-Revised (USDOL 1972, 1976, 1991). These 24, most vocationally significant, worker trait characteristics are listed below:
The 24 Most Vocationally Significant Worker Traits For MVQS2001 Job-Person Matching
General Educational Development Worker Traits
R - Reasoning
M - Math
L - Language
Aptitude Worker Traits
S - Spatial Perception
P - Form Perception
Q - Clerical Perception
K - Motor Coordination
F - Finger Dexterity
M - Manual Dexterity
E - Eye-Hand-Foot Coordination
C - Color Discrimination
Physical Capacity Worker Traits
PD1 - Lifting/Carrying/Pushing/Pulling/Sitting/Standing/Walking
PD2 - Climbing/Balancing
PD3 - Stooping/Bending/Crouching/Squatting/Kneeling/Crawling
PD4 - Reaching/Handling/Fingering/Feeling
PD5 - Talking/Hearing
PD6 - Seeing
Environmental Tolerance Worker Traits
EC1 - Work Location (Indoors/Both/Outdoors)
EC2 - Extreme Cold
EC3 - Extreme Heat
EC4 - Dampness/Humidity
EC5 - Noise/Vibrations
EC6 - Hazards (Mechanical/Electrical/Chemical/Heights)
EC7 - Fumes/Dusts/Mists/Gases/Odors
Updating the Year 2000 Vocational Quotient (VQ1)
Relationship between the Old VQ versus the Year 2000 VQ1
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The most comprehensive approach to bring order to the world of work and work adjustment, in terms of understanding Overall Job Difficulty and Maximum Vocational Potential, is the McCroskey Vocational Quotient (VQ). The Vocational Quotient was developed from the U.S. Department of Labor (US DOL) Job Analysis behavioral anchor ratings. There were 51 worker traits listed in the 1972 Handbook for Analyzing Jobs-Revised. In 1979, the 12,099 Job Titles described in the 1977 Dictionary of Occupational Titles (DOT; USDOL, 1977) were arranged by VQ, based on those 51 worker traits (McCroskey & Perkins, 1981), and published in the original four volumes of the Encyclopedia of Job Requirements (McCroskey, 1979a, 1979b, 1979c, 1979d).
The 51 worker trait raw scores for each nine-digit DOT job type were added together to produce a total or sum of scores. Some of these raw scores (N=20) had several possible scale values. For example, Reasoning (R), Math (M), and Language (L) had scores that ranged from one to six, and Spatial (S), Form Perception (P) and other aptitudes had scores ranging from one to five. Other worker traits (N=31) such as Seeing (Physical Demand #6) had only two possible values at the worker-trait level: a significant "1" or not significant "0" job requirement. The original Vocational Quotient (VQ) distribution had a mean of 57.1999 and a standard deviation of 14.4558 points.
The raw scores were divided into two groups based on whether they had three or more possible values (scalar; N=20), or two possible values (dichotomous; N=31). After recoding all worker trait profile values to place them on ascending scales, a multiple regression analysis was completed on the scalar variables to predict the Total Raw Score VQ (TRS-VQ). A second multiple regression was then completed using only the dichotomous variables to predict the TRS-VQ. The relevant acquired regression weights for each worker trait profile were multiplied by their corresponding worker trait profile values and summed to produce the Scalar Variables Vocational Quotient (SVVQ). The relevant acquired regression weights for each worker trait profile were also multiplied by their corresponding worker trait profile values and summed to produce Dichotomous Variables Vocational Quotient (DVVQ) estimates of overall job difficulty, as measured by the TRS-VQ criterion, for each job described in the 1977, 4th ed. DOT.
The final SVVQ (Rxy=0.99+ with TRS-VQ) distribution had a mean of 57.1998 and a standard deviation of 14.3741 points. The final DVVQ (Rxy=0.92+ with TRS-VQ) distribution had a mean of 57.2299 and a standard deviation of 13.3208 points. When the final sets of three Vocational Quotients (VQs) were printed to five decimal points, each unique worker trait / job requirements profile pattern was found to be associated with a unique and empirically precise set of VQs (McCroskey & Perkins, 1981).
Since 1979, all worker trait profiles and their VQs published in the original four volume edition of the Encyclopedia of Job Requirements (McCroskey, 1979a, 1979b, 1979c, 1979d) have been updated several times. They are now electronically incorporated in the McCroskey Dictionary of Occupational Titles (McDOT) and related McPLOT and MTSP programs. The final product of the first regression analysis (the SVVQ) was ultimately selected as the more robust and more precise estimate of the overall TRS-VQ. The SVVQ was therefore selected as the final, single-best, most representative, Vocational Quotient (VQ) estimate of overall job difficulty for each job.
In 1992, the VQ distribution was updated, recalculated, and transformed to produce a distribution with a mean of 100 and a standard deviation of 15 to provide consistency with the WAIS IQ distribution. People have IQs, Jobs have VQs. Put another way, VQ can be thought of as an IQ for work. When the final transformed VQ was printed to five decimal points, each unique job requirement pattern was found to be associated with a unique and empirically precise VQ.
In 1995, 2,408 internal DOT inconsistencies identified through research were corrected. This effected 1,913 of the 12,741 worker trait profiles for jobs described in the 1991 DOT. The VQ was re-calculated to adjust for these profile changes. Again, as expected, when the final VQ was printed to five decimal points, each unique job requirement pattern was again found to be associated with a unique and empirically precise VQ.
In 2000, the 12,775 worker trait profiles for jobs described in the McDOT2000 were recalculated based on data fusion of 75 selected O*NET 98 worker trait elements with the 24, most vocationally significant, McDOT 8.0R worker traits to reconstitute the McDOT 2000 5th edition DOT - Extended Dataset Edition. Both SVP and VQ aggregate variables were then re-calculated to adjust for the new, updated, Year 2000 worker trait level profile changes. In these re-calculations, only the 24, most vocationally significant (regardless of their scalar or dichotomous nature), worker trait values were used to determine the final SVP1 and VQ1 for each job. Again, as expected, when the final VQ1 was printed to five decimal places, each unique job requirement profile pattern was again found to be associated with a unique and empirically precise Vocational Quotient VQ1.
VQ (or VQ1), represents the Overall Job Difficulty level of Adaptive or Accommodative Behavior (in terms of Satisfactoriness and Satisfaction) required for people to accomplish meaningful Work Adjustment and develop Tenure for each of the 12,775 jobs described in the McCroskey Dictionary of Occupational Titles (McDOT2001; McCroskey, 2001).
Many studies have reviewed the use of the Vocational Quotient based on both the DOT and the O*NET. These studies included McCroskey & Lowe (1986, 1987), McCroskey (1991, 1992), McCroskey & Hahn (1995, 1997, 1998), (McCroskey, Hahn, Dennis & Streater (1995), McCroskey, Bohlke & Streater (1995), Hahn (1997), Dennis & Dennis (1998), McCroskey, Dennis & Dennis(1998), Hahn & Wells-Moran (1998), Dennis & Tichauer, (1998), Dennis & McCroskey (1999), McCroskey & Dennis (1999), Mayer (1998), and Dennis & McCroskey, (2000).
The Vocational Quotient (VQ) has been shown repeatedly to be a valid predictor of average starting and overall wages in California, Florida, Louisiana, Michigan, Minnesota, Idaho, Indiana, Iowa, Nebraska, North Carolina Virginia, Wisconsin, Washington, and other states. The Vocational Quotient (VQ) has been shown to be reliable and valid within and across independent cross-validation replication studies, longitudinal time frames (15+ years), and numerous geographic locations.
VQ has been repeatedly studied as a predictor of starting wages offered on Job Service Work Order Openings, overall average wages across all workers in the US, and average starting wages achieved by randomly selected rehabilitation clients at time of Status 26 closure in Indiana. VQ has been found to be highly predictive of average starting wages [(Rxy=0.91; SEE=$0.50/hr; McCroskey & Hahn (1998)], overall average wages across all workers in the United States [(Rxy=0.99+; SEE=$0.01/hr; McCroskey & Hahn (1998)], and average post-rehabilitation services starting wages of clients at time of Status 26 closure in Indiana [Mayer (1998, Rxy=0.68; SEE=$1.25/hr) and Dennis & McCroskey (2000, independent replication study Rxy=0.83; R2=0.70; SEE=$1.12/hr)].
Dennis & McCroskey (2000) independently replicated, expanded and updated Mayer’s (1998) Indiana labor market wage research, which was an update of her original study[19] of 132 randomly selected people that received State of Indiana Division of Disability, Aging, and Rehabilitation services and were placed in jobs in 1993 (Mayer, 1995). All clients in these studies met the criteria of being successfully rehabilitated. Mayer's 1998 MTSP 7.11R follow-up of her original study was replicated and expanded using MTSP 8.0R Program Earning Capacity Estimates.
Mayer (1998) found a gain of about $1.00 above the predicted average return-to-work wage for Indiana Rehabilitation clients based on MTSP 7.11R Program Earning Capacity Estimates. That gain was due in part to a small group of people with exceptionally high incomes. When those Outliers were removed in the Dennis & McCroskey (2000) follow-up study (Rxy=0.83; R2=0.70; SEE=$1.12 per hour), average return-to-work wage for Indiana Rehabilitation clients was about $1.00 below what had been predicted.
McCroskey & Dennis (2000), in an expansion of Mayer's 1998 study, included an analysis of Temperaments. The expanded study of Indiana Job Services openings and starting wages data from March, 1995 through February, 1996 compared income predictions when Temperaments or Personality variables were added to the MTSP VQ-Wage prediction formula. In the expanded study, Temperaments or Personality variables did not improve the VQ-Wage prediction sufficiently to overcome the increased variance inherent in these measures.
Building on previous research which assessed the validity of Vocational Quotient (VQ1) as a predictor of criterion referenced Job Service work order wages to be very positive, McCroskey, Hahn & Dennis (2000) established a new, expanded criterion-reference point distribution for MVQS2001 earning capacity estimation: six-point earning capacity prediction estimates. In their study[20], McCroskey, Hahn & Dennis (2000) evaluated the ability of the VQ1 to predict income reported for Occupational Employment Statistics (OES) job groups. Linear regression was used to predict reported income at the Mean, 10th, 25th, 50th, 75th and 90th percentile of the OES-Wage distributions. When VQ1 was used to predict to the middle of these six criterion-referenced distributions, it was found to be a very accurate predictor of each of these OES-Wage distributions reported by the US Department of Labor. Predictive Validity (Rxy) Coefficients were found to be 0.970, 0.973, 0.975, 0.974, 0.972 and 0.966, respectively. Standard Errors of Estimate (SEE) were found to be $1.19, $0.45, $0.69, $1.08, $1.65 and $2.66 per hour, respectively.
McCroskey, Hahn & Dennis (2000) recommended the expanded 6-point VQ1-OES Wage Algorithm, based on specific McDOT-VQ1[21] OES Wage Prediction, be used in the MVQS2001 Program to expand the range of predicted earning capacity estimates, increase overall reliability of predicted earning capacity estimates and reduce aggregate SEEs associated with prediction estimates. Their recommendations were peer-reviewed, found to be empirically sound, and subsequently implemented in the MVQS2001 Program (McCroskey, 2001).
Informal vs. Formal Job-Person Matching Theory
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In his book entitled Choosing a Vocation, Frank Parsons[22] (1909), known by many as the father of vocational guidance, postulated three primary requirements for effective vocational guidance:
1. A knowledge of the requirements and conditions for success in different lines of work, as well as related advantages and disadvantages, compensation, opportunities and prospects (knowledge of the world of work);
2. A clear understanding of the aptitudes, interests, ambitions, resources and limitations of the individual (self-knowledge and insight); and,
3. Systematic techniques for integrating these two sources of information in the vocational decision-making process (bringing the first two conditions together).
Parsons’ informal, yet profound, three-part theory for vocational guidance continues to guide the efforts of many theoreticians, researchers and clinical practitioners working to develop and refine the methodologies, techniques and tools necessary to provide better vocational counseling.
The Minnesota Theory of Work Adjustment (Dawis, England and Lofquist, 1964) provided formal (testable) foundational underpinning for all worker trait factor job person matching systems which later emerged. Many of these had their beginning in the late 1970s with the development of the Vocational Diagnosis and Assessment of Residual Employability [VDARE; (McCroskey, Wattenbarger, Field & Sink, 1977)], and continuing through the 1980s and 90s. These worker-trait-factor job-person matching TSA systems were all developed and computerized based on data describing job requirements in terms of the objectively defined behaviorally- anchored rating scales found in the Handbook for Analyzing Jobs-Revised (HAJ-R; USDOL, 1972; Reprinted, 1976; Re-revised 1991).
From 1900 to 1976, more than 20,000 mental and physical tests, covering a multitude of worker traits, had been developed and utilized in an effort to better understand individual differences in terms of basic human capacities and tolerances (Buros, eds. 1-8, 1938-1978). While many of these tests have been used as lone predictors of employability, research clearly supports the administration of a battery of vocationally relevant tests used in combination for better prediction of the multifaceted criteria known as individual employability (Anastasi, 1958, Anastasi, 1976, Bolton, 1976).
Flexible test batteries designed to allow for the systematic measurement of vocationally significant worker traits, remain a priority. Continuing efforts should focus on developing, refining and updating Ability and Work Context instruments and measures of Worker Traits/Job Requirements primarily in these four, vocationally-significant Worker Trait Factor areas:
1) General Educational Development, (3 worker traits)
2) Vocational Aptitudes, (8 worker traits)
3) Physical Capacities (6 worker traits, and
4) Environmental Tolerances (7 worker traits).
It is important that such measures be standardized with well-defined behavioral anchors, which are reliable, valid and interpreted in terms of relevant job requirements relative to general adult worker norms. Well-developed tests and measures with reasonable approximations of general adult worker norms can subsequently be combined into a test battery with their results combined and effectively utilized to accomplish Parsons’ (1909) third recommendation for matching people with jobs (McCroskey, Streater, Timming, Wattenbarger & Lowe, 1989; 1991).
The Minnesota Theory of Work Adjustment
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While informal Job-Person Matching Theory dates back to Parsons (1909), the Minnesota Theory of Work Adjustment (Dawis, England and Lofquist, 1964) provided the first formal foundational underpinning for all worker-trait-factor job person matching systems. These later emerged, beginning in the late 1970s with the development of the Vocational Diagnosis and Assessment of Residual Employability [VDARE; (McCroskey, Wattenbarger, Field & Sink, 1977)], and continuing through the 1980s and 90s. These worker-trait-factor job-person matching TSA systems were all developed and computerized based on data describing job requirements in terms of the objectively defined behaviorally-anchored rating scales found in the Handbook for Analyzing Jobs-Revised (HAJ-R; USDOL, 1972; Reprinted, 1976; Re-revised 1991).
Formal Propositions and Corollaries of the Minnesota Theory of Work Adjustment
The following was excerpted from The Minnesota Theory of Work Adjustment by Rene V. Dawis (Bolton, 1976).
The following propositions, designed by the authors [(Dawis, Lofquist & Weiss (1968), pp. 9-11)] to serve as a basis for research, state the Theory of Work Adjustment more formally:
Proposition I. An individual's work adjustment at any point in time is indicated by his concurrent levels of satisfactoriness and satisfaction.
Proposition II. Satisfactoriness is a function of the correspondence between an individual's abilities and the ability requirements of the work environment, provided that the individuals needs correspond with the reinforcer system of the work environment.
Corollary IIa. Knowledge of an individual's abilities and of his satisfactoriness permits the determination of the effective ability requirements of the work environment.
Corollary IIb. Knowledge of the ability requirements of the work environment and of an individual's satisfactoriness permits the inference of an individual's abilities.
Proposition III: Satisfaction is a function of the correspondence between the reinforcer system of the work environment and the individual's needs, provided that the individual's abilities correspond with the ability requirements of the work environment.
Corollary IIIa. Knowledge of an individual's needs and of his satisfaction permits the determination of the effective reinforcer system of the work environment for the individual.
Corollary IIIb. Knowledge of the reinforcer system of the work environment and of an individual's satisfaction permits the inference of an individual's needs.
Proposition IV. Satisfaction moderates the functional relationship between satisfactoriness and ability-requirement correspondence.
Proposition V. Satisfactoriness moderates the functional relationship between satisfaction and need-reinforcer correspondence.
Proposition VI. The probability of an individual being forced out of the work environment is inversely related to his satisfactoriness.
Proposition VII. The probability of an individual voluntarily leaving the work environment is inversely related to his satisfaction.
Combining Propositions VI and VII, we have:
Proposition VIII. Tenure is a joint function of satisfactoriness and satisfaction.
Given Propositions II, III, and VIII, this corollary follows:
Corollary VIIIa. Tenure is a function of ability-requirement and need-reinforcer correspondence.
Proposition IX. Work personality-work environment correspondence increases as a function of tenure. (pp. 234-235).
Basic Concepts of the Minnesota Theory of Work Adjustment
In an effort to simplify and further explain The Minnesota Theory of Work Adjustment, Dawis (In: Bolton, 1976), said:
Speaking at a simple level, a theory is an account of what is happening or what has happened. The Theory of Work Adjustment, then, is an account of what is happening or what has taken place in work adjustment. As an account, the theory is itself, quite simple.
Tenure, Satisfaction, and Satisfactoriness
When a person goes to work, one of the first objective observations that can be made is that he/she continues on the job for a certain length of time. Tenure, length of time on a job, is a basic concept of the Theory of Work Adjustment. Tenure implies a minimal level of work adjustment in terms of correspondence between Satisfactoriness and Satisfaction. If an employee's work adjustment were to drop below this level, then it is presumed that he/she would be let go (fired) from, or would otherwise leave (quit), the job.
. . .
Tenure, satisfaction, and satisfactoriness, then, are the basic outcomes, or dependent variables, of work adjustment. To the extent that work adjustment has taken place, tenure, satisfaction, and satisfactoriness would be manifested to some commensurate extent. That is, they are indicators of work adjustment. These indicators point to the basic factors involved in work adjustment. Satisfaction suggests factors on the individual side, while satisfactoriness suggests factors on the work side (viewing work adjustment as what happens when a person goes to work)...." (pp. 229-230).
Concepts Linked to Measures Under the
Minnesota Theory of Work Adjustment
The Minnesota Theory of Work Adjustment provided formal foundational underpinning for all worker-trait-factor job person matching systems which later emerged.
Worker Trait Factors, Worker Traits and Worker Trait Elements are operationalized as Worker Characteristic/Job Requirement component elements on the Job Satisfactoriness, Abilities, Ability Requirements and Occupational Aptitude Pattern (OAP) side of the Minnesota Theory of Work Adjustment equation.
Worker Interests, Temperaments, Attitudes, Satisfaction, Needs, Values and Occupational Reinforcer Patterns (ORP) are operationalized as Worker Characteristic/Job Requirement component elements on the Job Satisfaction, Worker Needs and Work Reinforcer Systems side of the Minnesota Theory of Work Adjustment equation.
Perhaps Dawis (Ch. 13, In: Bolton, 1976, pp. 227-248) said it best:
A formal test of a theory requires that the theory's concepts be operationalized, i.e., stated in terms precisely and specifically describing the operations by which observations are to be made in order to confirm or to disconfirm the theory or any part of it. This requirement is usually fulfilled through the use of instruments in data collection. (p. 235).
For the Theory of Work Adjustment, six instruments would be needed to make the requisite observations, measures of the following six concepts (p. 234-240):
Concepts Instruments/Measures*
1) Satisfactoriness, Minnesota Satisfactoriness Scales (MSS)
2) Satisfaction, Minnesota Satisfaction Questionnaire (MSQ)
3) Abilities, General Aptitude Test Battery (GATB)
Related Extensions
*Maximum Least Demonstrated Worker Traits
Functioning across Successfully Demonstrated
Work History, extracted using the Vocational
Diagnosis and Assessment of Residual
Employability (VDARE) Process which was
based on Worker Traits/Job Requirements
Profiles rated on HAJ behaviorally anchored
Job Analysis Scales identified in the Realistic
Occupational Counseling (ROC) Handbook, or
the Encyclopedia of Job Requirements (EOJR).
*Many Aptitude, Achievement, & Ability test
results crunched with the McPLOT Program.
*Physical Capacities, Environmental Tolerances
rated on Handbook for Analyzing Jobs (HAJ)
behaviorally anchored Job Analysis Scales.
4) Ability Requirements, Occupational Aptitude Patterns (OAPs)
Related Extensions
*Worker Traits/Job Requirements Profiles
rated on HAJ behaviorally anchored Job
Analysis Scales identified using the Realistic
Occupational Counseling (ROC) Handbook, or
the Encyclopedia of Job Requirements (EOJR).
5) Needs, and MN Importance Questionnaire (MIQ)
Related Extensions
MVQS Occupational Values & Needs Inventory
6) Reinforcer Systems MN Job Description Questionnaire (MJDQ)
~Occupational Reinforcer Patterns (ORPs)
Related Extensions
MVQS Vocational Interest & Personality
Reinforcer (VIPR) Type Indicator
Measures of satisfactoriness and satisfaction would be the outcome or criterion measures. (Tenure is an outcome variable, too, but this can be observed without the need for instrumentation.)
Measures of abilities and needs would be required to describe the person, while measures of ability requirements and reinforcer systems would be needed to describe the work environment.
To enable the measurement of correspondence, one approach would be to develop parallel measures of people and work environments; that is, measures of abilities and ability requirements should utilize the same set of ability dimensions, and likewise, measures of needs and reinforcers should utilize the same set of reinforcement dimensions. This approach was followed in the Work Adjustment Project. . . . (pp. 234~240).
* [Selected emphases and Instruments/Measures added].
Original Extensions of the Minnesota Theory of Work Adjustment
Work adjustment (i.e., the achieving and maintaining of individual- environmental correspondence) is an interactive process. Work adjustment mechanisms involving Correspondence, Discorrespondence, Flexibility, Activeness, Reactiveness, and Rate of Work Adjustment, on the part of both the individual and the work environment, were early extensions of the theory, which were present, operationally definable, and observable, relative to testable hypotheses regarding their impact on work adjustment over time.
The Realistic Occupational Counseling (ROC) Handbook (Wattenbarger & McCroskey, 1978) was the first private sector supplement to the 1965 Dictionary of Occupational Titles. It provided the original modal worker trait factor profiles used for work history analysis and post-injury residual employability job-person matching using the VDARE Process. The 114 modal worker trait job requirement profiles in the ROC Handbook provided the original database for the Realistic Occupational Counseling Computerized Job-Person Matching Transferable Skills Analysis (TSA) Program. The ROC TSA Program was the first worker trait factor job-person-matching program developed for use on mainframe computers at the University of Georgia (Wattenbarger & McCroskey, 1978).
Other Extensions of the Theory
Research on other Minnesota Theory of Work Adjustment Extensions (e.g., concepts, constructs, link relatives, occupational values and needs, vocational interests and personality reinforcer type indicators) impacting on our understanding of work adjustment have been operationally defined, studied and found supportive of Propositions identified in the Minnesota Theory of Work Adjustment.
Other Minnesota Theory of Work Adjustment Extensions include, but are not limited to, Differential:
1) VDARE Residual Employability Profiling (McCroskey, Wattenbarger, Field & Sink, 1977.
2) Vocational Potential Profiling in SSA Disability Determination (Wattenbarger, 1981).
3) The Vocational Quotient (VQ) as a Differential Measure of Overall Job Difficulty and Maximum Vocational Potential (McCroskey & Perkins, 1981).
4) Job Value (McCroskey & Lowe, 1986, 1987).
5) Test Validity (McCroskey & Perkins, 1981; McCroskey, Streater, Timming, Wattenbarger & Lowe, 1989; 1991).
6) Job Service Work Orders Starting Wage Prediction (McCroskey & Lowe, 1987).
7) Rehabilitation Clients Return-to-Work Wage Prediction (Mayer, 1995).
8) Overall Average and Typical Starting Wage Prediction (McCroskey, 1992)
9) Earning Capacity Link Relatives (ECLRs) to Enhance Pre-Injury Earning Capacity Prediction at the Local Labor Market Level (McCroskey, 1992, 1997, 1998, 2000).
10) Earning Capacity Link Relatives (ECLRs) to Enhance Post-Injury Earning Capacity Prediction at the Local Labor Market Level. (McCroskey, 1992).
11) Six point (Mean, 10th, 25th, 50th [Median], 75th and 90th Percentile) wage earning capacity criterion-referenced relative to National Occupational Employment Statistics (OES) prediction estimates (McCroskey, Hahn & Dennis, 2001).
12) The Occupational Values and Needs Inventory (McCroskey, 2001 - modeled after the original Minnesota Importance Questionnaire and criterion-referenced relative to specific 9-digit McDOT 5th Edition DOT Job Types).
13) The Vocational Interest and Personality Reinforcer (VIPR) Job Type Indicator (McCroskey, 2001 - modeled after Jung-based People Personality Types and criterion-referenced relative to specific 9-digit McDOT 5th Edition DOT Job Types, cross-walked from corresponding Jung-based People Personality Types).
From Manual to Computerized Job-Person Matching
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Job-Person Matching Systems initially began with manual matching systems. Botterbusch (1986) informed us that efforts to develop job-person matching systems as we know them today, actually began in the mid-1950s when Job Service personnel developed several manual systems for matching General Aptitude Test Battery (GATB) test results with jobs.
By the late 1970s, all three of Parsons (1909) informal tenets had been achieved in much detail with the arrival of the Vocational Diagnosis and Assessment of Residual Employability (VDARE) Process (McCroskey, Wattenbarger, Field & Sink, 1977).
The VDARE Process was based squarely on Proposition II and Corollary IIb with reliance on Proposition III and Corollary IIIb of the Minnesota Theory of Work Adjustment (Dawis, England and Lofquist, 1964; Formally restated and expounded on through supporting research by Dawis, R.V., 1976, In: Bolton, 1976).
VDARE became an effective tool in the hands of vocational experts around the country. This was especially true for Expert Witness testimony in Social Security Disability Claims, where reference to previously demonstrated work history, residual functioning, and transferable skills were major considerations [Botterbusch (1986)].
In 1978, the zeitgeist was ready for improvement and better utilization of existing job-person-matching systems through the much more efficient use of computers (McCroskey, Streater, Timming, Wattenbarger & Lowe, 1989; 1991). In 1978, the ROC TSA became the first mainframe computerized job person matching system. It was developed at the University of Georgia (Wattenbarger & McCroskey, 1978). It was used primarily as a tool for reliable vocational expert analysis of Social Security Disability Insurance (SSDI) applicant appeal cases. Primary considerations for these analyses included age, education, past relevant work history and work restrictions stemming from medical and/or psychological disabilities.
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With the advent of personal computers in the early 1980s, the Datamaster Transferable Skills Analysis (TSA) Program (McCroskey, 1982) was developed, with many revisions and updates to follow (McCroskey, 1982,1983, 1985, 1987, 1989 & 1990). It was the first micro-computerized worker-trait-factor job-person matching TSA system designed specifically for use on Personal Computers. Others soon followed.
Comparing Computerized Job-Person Matching Systems
Botterbusch (1983) identified, described and compared eight computerized worker-trait-factor job-person-matching systems. In his update, Botterbusch (1986) identified, described and compared 15 such programs. Brown, McDaniel, Couch and McClanahan (1994) expanded on the earlier works of Botterbusch in their publication entitled: Vocational Evaluation Systems and Software: A Consumer’s Guide.
Dennis & Dennis (1998) in their article, Job Search Software under Daubert, informed us that:
In the 1993 Daubert decision, the United States Supreme Court established scientific knowledge as the standard for admissibility for expert testimony (Feldbaum & McCroskey, 1995, Feldbaum, 1997). This standard can be anticipated to have a significant impact on psychological, rehabilitation, vocational and economic experts. One general expectation is that the instruments used to assess disabilities and predict their consequence will need to be reliable (provide consistent results), valid (measure what it is expected to measure) and accurately predict outcomes with reasonable certainty and known acceptable error rates (accuracy of predictions).
The developers of Job Search Software listed by Brown, McDaniel, Couch and McClanahan (1994) were interviewed by phone to determine the scientific attributes of their software. Where available, relevant research to their products was reviewed as well. The responses of the vendors to the possibility of Daubert restricting the use of their software were varied. All the respondents were aware of the 1993 Daubert decision. Only two programs were found to have any research regarding reliability, validity and error rate issues addressed in the Daubert decision. Some expected there to be major upheavals in the future. Others took a more conservative or wait-and-see attitude.
Dennis & Dennis (1998) found one program, the McCroskey Vocational Quotient System Transferable Skills Analysis Program (MVQS MTSP) to have 50+ validity research publications, since 1986 to date and continuing. MTSP was underpinned with on-going scientific research designed to address vitally important issues. These included Reliability, Predictive Validity, and Standard Error of Estimate rates, identified by the US Supreme Court in the Daubert decision, as being the key criteria to be used by judges in their roles as gatekeepers for determining admissibility of expert witness testimony.
Clearly, many decades of patience, research and development have begun to produce a fruitful realization of Parson’s intuitive direction. Efforts must continue with the collection, analysis and synthesis of on-going research, into renewed development of vocational theory and practice. Theories must be refined through research. New tools for more efficiently and effectively matching workers with jobs must continue to be developed and updated. New hypotheses must be empirically tested through research on those tools. Results of those studies must be published in peer-reviewed journals to keep our peers abreast of the research evidence if we are to continue understanding, refining and providing evidence of the reliability and validity of our theories to the courts and other interested parties.
The O*NET 98 Transferable Skills (TS) Paradigm
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The 1998 USDOLETA-O*NET 98 Transferability of Skills Paradigm in the MVQS MTSP 1998/2000/2001 Transferable Skills Analysis (TSA) Super Sort?
In 1998, 5- or 6-character Occupational Unit Classification (OUC) Coded Transferable Skills Groups (often referred to as O*NET 98 TS Code Groups) were developed for O*NET 98. The O*NET 98/OUC TS Code Groups were derived from USDOL Occupational Employment Statistic (OES) Codes (which are identified by the first 5 digits, of the 5-digit or 6-character OUC Codes, found in Section 7, Part 2, of the MTSP 8.0R and MTSP 2000/2001 TSA Program Job Profile Reports).
OES Codes were empirically studied using Cluster Analysis for purposes of establishing O*NET 98 Transferable Skill (TS) Groups. Outliers (jobs which didn't belong) were statistically identified using Euclidean Distance Measures coupled with Ward's Minimum Variance Method (Ward, 1963) and reclassified into OES groups or subgroups, or reassigned to other groups or subgroups, as necessary to assure:
1) Belongingness (where the work activities of each 9-digit DOT coded occupation had to match the definition of the occupational category under which it was grouped),
2) Homogeneity (where differences within a single category had to be less than differences between categories and all 9-digit DOT coded occupations within a single category had to be less than differences between categories and all the 9-digit DOT coded occupations within a single category had to show consistency of skill transferability),
To accomplish Belongingness and Homogeneity, the three lone variables (MPSMS, METWA and SVP), previously used by the United States Department of Labor Employment and Training Administration (USDOLETA) to conceptually define their Old Transferability Of Skills Paradigm, were, in 1998, operationally redefined with 28 Occupational Classification Codes, Worker Traits, Temperaments and Aggregate variables in their New Expanded Transferability Of Skills Paradigm.
O*NET 98 Transferable Skills Groups
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As a result of the Cluster Analyses which were completed and finalized for the new O*NET 98 Transferable Skills Groupings, 1,172 Occupational Unit Classification (OUC) Groups, or, as they have become better known, O*NET 98 Code Transferable Skills (TS) Groups, were created.
O*NET Code TS Groups were based on USDOL Occupational Employment Statistics (OES) Code Groups, which are identified by the first 5 digits, of each 5-digit or 6-character O*NET 98 Code TS Group. Thus, OUC/O*NET Code TS Groups are highly refined, empirically derived Transferable Skills Subgroups, within the OES Code Group Classification Structure.
Of the 1,172 identified O*NET 98 Code TS Groups, Means Data Profiles for 1,122 were reported in the US DOLETA O*NET 98 Version 1.0 Program. Researchers at Vocationology, Inc. constructed Means Data Profiles for the remaining 50 O*NET 98 Code Groups (not reported in the US DOLETA O*NET 98 Version 1.0 Program), and added two new groups (each containing only 1 job), bringing the total N to 1,174 groups. Vocationology researchers also reconstituted 12 jobs which were reclassified with different 9-digit DOT Codes by O*NET 98 researchers.
• In the McDOT2001 program, there are 12,775 specific unduplicated 9-digit DOT-Coded Jobs and 12,811, 9-digit DOT-Coded Jobs contained in the McDOT 2000 Crosswalk when duplicated jobs are included. In McDOT2001 each job has a specific worker traits/job requirements profile with respect to the 24 vocationally significant worker traits and 3 aggregate variables (VQ, SVP and ZONE).
• In the O*NET 98 Version 1.0 Viewer Program, there were 12,761, 9-digit DOT-Coded Jobs contained in the O*NET 98 DOT Crosswalk of unduplicated jobs (1,124 of which means data element profiles are not viewable in the O*NET 98 Viewer) and 12,797, 9-digit DOT-Coded Jobs contained in the O*NET 98 DOT Crosswalk, when duplicated 9-digit DOT-Coded Jobs are included.
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A total of 1.3 percent of the OUC/O*NET Code TS groups (N=15) constitute 38 percent (N=4,889) of the 12,811 (counting all duplications), 9-digit DOT coded jobs. Such a large collection of jobs within so few OU Code groups drastically limits how precise you can be about specific jobs, job tasks, or work sites. The O*NET 98 Occupational Unit (OU) Code by DOT job count distribution is a grossly skewed distribution, which clearly requires job-person matching be accomplished at the job specific worker traits/job requirements profiles level, if we are to avoid overstating transferable skills for any given client.
The type of downsizing accomplished in the development of O*NET 98 (Version 1.0) Program by failing to reanalyze specific 9-digit DOT-Coded jobs was neither theoretically nor practically sound. Analyzing O*NET TS groups of jobs and reporting group means data only, may have been cost-efficient for O*NET, but their failure to collect and deliver specific job analysis data has not been good for vocational experts and related vocational professionals, who need job specific, not grouped means, data. While their development of O*NET TS Groups deserves a great deal of credit, they should have stuck with the original plan and developed a 5th edition DOT versus trying to replace it.
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MVQS2001 MTSP Transferable Skills Analysis (TSA) Valence Levels
The 1998 US DOLETA-O*NET 98 Transferability of Skills Paradigm was expanded to include Percent of Transferability (Valence) and incorporated in the MTSP 8.0R Program on 10/15/98. It was included in the MTSP 2000 Transferable Skills Analysis (TSA) Super Sort on 01/01/2000. Following the very high validity findings identified in the Grimley, Williams, Hahn & Dennis (2000) validation study[23], it was included as a part of the MVQS2001 MTSP Transferable Skills Analysis (TSA) Super Sort on 01/01/2001.
Percent of Transferable Skills Valence Level of Transferable Skills
80 - 97% 5 - High Percentage of Skills
60 - 79% 4 - Moderate Percentage of Skills
40 - 59% 3 - Low Percentage of Skills
20 - 39% 2 - Skills Required Not Available
00 - 19% 1 - Skills Not Required
The Expanded MVQS2001 MTSP Transferable Skills (TS) Paradigm
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The Expanded MVQS2001 Transferability of Skills Paradigm includes consideration of the same 28 codes and scales used for developing the 1,172 O*NET TS Groups:
1) Primary Materials, Products, Subject Matter and Services (MPSMS) code,
2) Secondary Materials, Products, Subject Matter and Services (MPSMS) code,
3) Tertiary Materials, Products, Subject Matter and Services (MPSMS) code,
4) Primary Work Field: Machines, Tools, Equipment and Work Aid (MTEWA) code,
5) Secondary Work Field: Machines, Tools, Equipment & Work Aid (MTEWA) code,
6) Tertiary Work Field: Machines, Tools, Equipment and Work Aids (MTEWA) code,
7) Specific Vocational Preparation (SVP),
8) (D)ata Complexity,
9) (P)eople Complexity,
10) (T)hings Complexity,
11) General Educational Development: (R)easoning,
12) General Educational Development: (M)ath,
13) General Educational Development: (L)anguage,
14) (G)eneral Learning Ability Aptitude,
15) (V)erbal Aptitude,
16) (N)umerical Aptitude,
17) (S)patial Perception Aptitude,
18) (P) Form Perception Aptitude,
19) (Q) Clerical Perception Aptitude,
20) (K) Motor Coordination Aptitude,
21) (F)inger Dexterity Aptitude,
22) (M)anual Dexterity Aptitude,
23) (E)ye-Hand-Foot Coordination Aptitude
24) (C)olor Discrimination Aptitude
25) (D)irecting Temperament,
26) (P)eople Temperament,
27) (I)nfluencing Temperament, and
28) (E)xpressing Temperament.
Theory, Reliability, Predictive Validity and Error Rates Associated with the VDARE Process and MVQS Vocational Analysis
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Theoretical Underpinning: VDARE Vocational Analysis
Under the VDARE Vocational Analysis Process, Proposition I of the Minnesota Theory of Work Adjustment is assumed to be true, therefore:
• The VDARE Vocational Analysis Process is based squarely on Proposition II and Corollary IIb with reliance on Proposition III and Corollary IIIb of the Minnesota Theory of Work Adjustment (Dawis, England and Lofquist, 1964; Formally restated and expounded on through supporting research by Dawis, R.V., 1976, In: Bolton, 1976).
Theoretical Underpinning: MVQS Vocational Analysis
The MVQS Vocational Analysis Process relies heavily on the VDARE Vocational Analysis Process, and thus, under MVQS Vocational Analysis Process, Proposition I of the Minnesota Theory of Work Adjustment is also assumed to be true, therefore:
• The MVQS Vocational Analysis Process is also based squarely on Proposition II and Corollary IIb with reliance on Proposition III and Corollary IIIb of the Minnesota Theory of Work Adjustment (Dawis, England and Lofquist, 1964; Formally restated and expounded on through supporting research by Dawis, R.V., 1976, In: Bolton, 1976).
Reliability, Validity and Error Rates for the VDARE Process
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Research supports the following Reliability, Validity and Error Rate statistics as applicable to the VDARE Process and to the MVQS Vocational Analysis Process (which incorporates and expands VDARE using the McDOT, McPLOT and MTSP Programs), with reasonable vocational, rehabilitation economic and statistical certainty:
• Inter-Rater Reliability Using the VDARE Vocational Analysis Process - Three-Way Inter-Rater Reliability for using the VDARE Process for Residual Employability Profiling has been found to be in the Extremely High range at Rxxx=0.9944 (McCroskey, 1979).
• Predictive Validity & Known Error Rates Using the VDARE Process - In a dissertation level validation study on the VDARE Process, McCroskey (1979), found support for the implications in Proposition II, Corollary IIb, Proposition III and Corollary IIIb, that maximum least demonstrated satisfactoriness and satisfaction assumptions, reliably derived and implied (Rxxx = 0.9944) from residual employability worker traits/job requirements profiles of successful client work history, modified by medical restrictions, provided excellent prediction [(93.3% (without testing) and 96.1% (with testing) agreement, with an error rate from 3.8% (with testing) and 8.4% (without testing)] of post rehabilitation services job requirement profiles of jobs at time of placement, in which tenure ensued. A series of follow-up validation studies (Burge, 1978; Field, McCroskey, Grimes & Wattenbarger, 1978; Knowles, 1978; Reinhardt, 1978; Teal, 1978; and Wattenbarger, 1981) with similar findings regarding the validity of the VDARE Process were described in [McCroskey & Perkins (1981), pp. iii-iv & 41-44].
• Vocational Potential in SSA Disability Determination Using VDARE - In a second dissertation level validation study of the VDARE Process, Wattenbarger (1981), found support for Proposition II, Corollary IIb, Proposition III, and Corollary IIIb of the theory, that maximum least demonstrated satisfactoriness and satisfaction assumptions, reliably derived and implied from residual employability worker traits/job requirements profiles of successful client work history, modified by medical restrictions, provided excellent prediction of Social Security Administration (SSA) eligibility decisions made using the SSA Grid System. In his case review research, Wattenbarger compared independent hypothetical findings based on the VDARE Process, with actual eligibility decisions made by Georgia Disability Determination Unit (DDU) examiners. He found 67% agreement with DDU examiners Grid System based decisions and 33% disagreement with their decisions.
Reliability, Validity and Error Rates for the MVQS Vocational Analysis Process
[pic]
• Inter-Rater Reliability Using the MVQS Vocational Analysis Process: Three-Way Inter-Rater Reliability for using the MVQS McDOT, McPLOT and MTSP Programs in tandem has been found to be in the Extremely High range at Rxxx=0.9864 (McCroskey, Smolarski & Haskins, 1995).
• Predictive Validity and Known Error Rate Using VQ-Wage Data: Predictive Validity associated with Pre- and Post-Injury VQ-Wage Earning Capacity Predictions relative to Job Service Work Order Openings and Wage Offered data has been found to be Extremely High at around Rxy=0.91, with an error rate (SEe=$0.50/hr) of plus or minus $0.50/hr with 67% confidence and plus or minus $1.00/hr with 95% confidence. (McCroskey & Hahn, 1998, McCroskey, 2000).
• Predictive Validity & Known Error Rate Using VQ-OES Wage Data: Predictive Validity associated with Occupational Employment Statistics (OES) Employment and Wage Estimates has been found to be Very High at Rxy=0.68, with a known error rate (SEe=$1.01/hr) of plus or minus $1.01/hr with 67% confidence and plus or minus $2.02/hr with 95% confidence (Dennis & McCroskey, 1999; McCroskey & Dennis, 1999).
Validity Studies: The MVQS Vocational Quotient (VQ) as a Predictor of Earning Capacity
[pic]
In their study, Dennis & Dennis (1998) identified one program (MVQS MTSP) with 50+ validity research publications, since 1986 to date and continuing (See graphic representations below). Researchers at Vocationology, Inc., are aggressively moving forward with on-going scientific research to address the vitally important issues pertaining to Inter-Rater Reliability, Predictive Validity, and known Standard Error of Estimate rates identified by the US Supreme Court in the Daubert decision, as being the key criteria, to be used by judges in their gatekeeper role, for determining admissibility of expert witness testimony.
Graphically displayed below are three figures summarizing the results from the majority of the 50+ studies which have been completed and presented in white paper presentations at national conferences, workshops, seminars, and/or published in books or national peer-reviewed journals between 1986 and 1999:
[pic]
Removal of Outliers
As reflected in the above graph, in 1997 these regression analysis studies began removing statistical Outliers (standard method, where the Actual Wage was greater than + or - 2 Standard Deviations of the Predicted Wage) from the VQ-Wage data distributions. This resulted in significant improvements in predictive validity coefficients (Rxy) and coefficients of determination (R2), along with corresponding decreases in standard errors of estimates (SEE) for prediction estimates within the + or - two standard deviations of the regression line of best fit (95% Confidence Level).
[pic]
The above graph depicts the improvements in Predictive Validity (Rxy) and Coefficients of Determination (R2) achieved over time.
[pic]
In reviewing the above graphical representations of 50+ Predictive Validity research studies, it is clear that VQ-Wage Predictive Validity Coefficents (Rxy), Coefficients of Determination (R2), and Standard Errors of Estimate (SEE) have improved over time (from High-Level in 1986, to Extremely High-Level Validity by the late 1990s). The most recent MVQS MTSP combined 7-state (California, Florida, Louisiana, Minnesota, Virginia, Washington & Wisconsin) studies confirm these trends as continuing patterns.
Using MTSP2001 Job Bank Filters to Predict State Job Types and Job Openings: Reliability, Validity and Error Rates
Data used in the analysis of the reliability, validity and error rates of using MTSP2001 Job Bank Filters to Predict State Job Types and Job Openings was collected from Work Force Development Centers covering seven States. Only the most current data available was used to assure reasonable timeliness of the prediction. The Seven State Job Bank databases containing specific MVQS 9-digit McDOT Coded Job Types and Job Openings used in this study were compiled from the seven Database Sets indicated below:
1. California Data = Fiscal Year 1999.
2. Florida Data = Program Year 1999.
3. Idaho Data = 4th quarter 1999, 1st, 2nd and 3rd quarters 2000.
4. Louisiana Data = Fiscal Year 1999.
5. Minnesota Data = 4th quarter 1997, 1st, 2nd and 3rd quarters 1998.
6. North Carolina Data = Program Year 1999.
7. Virginia Data = Fiscal Year 1999.
Tabled Summary Data
Table 1[24]
|Table 1: Actual DOTCodes vs. Predicted DOTCodes - Accuracy & Error in MVQS2001 Job Banks |
| | | | | | | | | |
| | |CA |FL |ID |LA |MN |NC |VA |
| Actual DOTCodes: | 5,650| 4,147 | 2,318 | 2,022 | 2,861 | 4,716 | 3,060 |
| Predicted DOTCodes: | 3,033| 2,399 | 1,686 | 1,350 | 1,898 | 1,956 | 1,963 |
| Percent Accuracy: |53.68 |57.85 |72.74 |66.77 |66.34 |41.48 |64.15 |
| Percent Error: |46.32 |42.15 |27.26 |33.23 |33.66 |58.52 |35.85 |
| | | |Mean Percent of DOT Codes Accurately Predicted: |60.43 |
| | | |Mean Percent of DOT Codes Not Predicted (Error): |39.57 |
Table 2
|Table 2: Actual Openings vs. Predicted Openings - Accuracy & Error in MVQS2001 Job Banks |
| | | | | | | | | |
| | |CA |FL |ID |LA |MN |NC |VA |
| Actual Openings: | 1,908,434 | 240,961 | 152,721 | 76,887 | 105,625 | 308,025 | 182,733 |
| Predicted Openings: | 1,899,700 | 221,543 | 149,321 | 69,525 | 102,800 | 242,964 | 149,853 |
| Percent Accuracy: |99.54 |91.94 |97.77 |90.42 |97.33 |78.88 |82.01 |
| Percent Error: |0.46 |8.06 |2.23 |9.58 |2.67 |21.12 |17.99 |
| | | |Mean Percent of Job Openings Accurately Predicted: |91.13 |
| | | |Mean Percent of Job Openings Not Predicted (Error): |8.87 |
Table 3: MVQS MTSP2001 Job Banks Accuracy
| | |CA |FL |ID |LA |MN |NC |VA |
| |Opens |99.54 |91.94 |97.77 |90.42 |97.33 |78.88 |82.01 |
| |Titles |53.68 |57.85 |72.74 |66.77 |66.34 |41.48 |64.15 |
| | | | | | | | | |
Figure 1: MTSP2001 Job Banks Accuracy
Conclusions
On average, MTSP2001 State Job Banks captured 60.43% of the 9-digit McDOT Coded DOT Job Types (See above, Table 1), which, on average, represented 91.13% of the Job Openings (See above, Table 2) found in the Seven State Job Banks used in this study. These findings fit normal expected representation patterns quite well and lend strong support for predictive validity generalization of the identified very high levels of validity, reliability and representative content of all MVQS MTSP2001 Job Banks.
Filename: C:\My_Documents\States7.doc
The Four Jung People-based Personality Scales and
Preferences typically associated with those Scales:
1. Energizing - How a person is energized[25]
1. Extroversion (E): Preference for drawing energy from the outside world of people, activities or things.
2. Introversion (I): Preference for drawing energy from one's internal world of ideas, emotions, or impressions.
2. Attending - What a person pays attention to
3. Sensing (S): Preference for using the five senses to determine what is real.
4. Intuition (N): Preference for using the imagination to envision what is possible - to look beyond the five senses[26].
3. Deciding - How a person decides
5. Thinking (T): Preference for organizing and structuring information to decide in a logical, objective way.
6. Feeling (F): Preference for organizing and structuring information to decide in a personal, value-oriented way.
4. Living - What Lifestyle a person prefers[27]
7. Judgement (J): Preference for living a planned and organized life.
8. Perception (P): Preference for living a spontaneous and flexible life.
Interpreting VIPR Vocational Personality Types Relative to Jung-based People Types
The sixteen Vocational Interest and Personality Reinforcer (VIPR) Types represent clusters of jobs, which Jung People-Based Personality Types of the same or similar persuasion tend to enjoy doing. The VIPR Type job reinforcers are similar to the personality reinforcer preference tendencies of the various Jung People-Based Types. It is important to remember that MTSP Job Profile Reports do not list all possible jobs under the headings, only those which match the client's post vocational potential profile.
It is very important to remember that people can, and frequently do, fill jobs in VIPR Type clusters that are dissimilar to their Jung People Personality Type... this happens all the time... and sometimes works out quite well.
VIPR Type Job Clusters are sorted in descending order of Client Values Agreement (VA) to provide clients of the same Jung People-based Personality Type, ordered lists of job matches they would typically tend to enjoy. Put another way, the Job at the top of any given VIPR Type list not only matches client Vocational Potential Profile on the 24 most vocationally significant worker traits, but would also tend to satisfy client Occupational Values and Needs more than any other job down the list.
Excerpts from the US Department of the Interior (DOI) Web Site[28] Describing Personality Instruments and their Potential Vocational Uses
"Personality instruments are tools that give continuing insight into ourselves and others. They are frequently used to help individuals see their preferences, potential strengths and weaknesses, and how they relate to different occupations. They can be a powerful tool in helping an individual select a potentially satisfying occupation and/or field of study.
Two of the most well-known personality instruments are the Keirsey Temperament Sorter[29] and the Myers-Briggs Type Indicator®[30]. Both deal with four very strong categories for taking in and processing information, plus interacting with the world[31]. These instruments are based on the work of the Swiss psychiatrist, Carl Jung.
This unit uses the Keirsey Temperament Sorter to identify a basic personality type. You may then use this information to direct you to different careers.
Before completing the Keirsey, it is important to be aware of some important points:
• The Keirsey measures preferences, not skills. We can all do things we do not prefer. This is about what you do when you have your druthers.
• There are no right or wrong responses, only those that fit you and those that do not!
• One personality type is not better than another. Each has a richness and potential as great as the others. You are the final judge.
• After you receive your 4-letter type, you'll be able to weigh whether the description fits you and make changes. Read an explanation of what the letters represent." (See next Page).
Definitions Relating to Personality Type (P-Type) Letter Designations
|What Do Those Letters Represent...?[32] |
|Refers to how a person is energized |
|Extraversion |Introversion |
|Shows a preference for drawing energy from the outside word of |Shows a preference for drawing energy from one's internal world of |
|people, activities or things. |emotions or impressions. |
|Refers to what a person pays attention to |
|Sensing |iNtuition |
|Shows a preference for trusting information received through the five|Shows a preference for trusting information received through a "sixth|
|senses and noticing what is actual. |sense" and noticing what might be. |
|Refers to what a person most trusts when making a decision |
|Thinking |Feeling |
|Shows a preference for trusting logical and objective information. |Shows a preference for trusting |
| |personal and value-oriented |
| |information. |
|Refers to the life style a person adopts |
|Judgment |Perception |
|Shows a preference for living |Shows a preference for living a spontaneous and flexible life. |
|a planned and organized life. | |
Selected Additional Background Information, Insight and Recommendations Posted on the US Department of the Interior (DOI) Web Site Regarding Connecting Personality Types With Careers and Jobs
| |Connecting Personality Types With Careers and Jobs[33] |
|Before looking at the lists below... |
|The lists represent careers and jobs people of various types tend to enjoy doing. The job requirements are similar to the |
|personality tendencies of the various types. It is important to remember that these do not list all the jobs possible under the |
|headings. And it is very important to remember that people can, and frequently do, fill jobs that are dissimilar to their |
|personality... this happens all the time... and sometimes works out quite well. |
| |
|Why then should we even consult these lists? |
|The lists are just another tool to give you ideas about careers and jobs you might enjoy. Use the lists as [a] tool, not a box! |
| |Source: careerwebmaster@ios. |
| |U.S. Department of the Interior |
| |Revised: Monday, 06-Nov-2000 09:42:48 EST |
| |(Source Web Site: ) |
Partial Lists of Extravert Reinforcer Careers and Jobs from the US Department of the Interior (DOI) Web Site
|ESTP |ESFP |ENFP |ENTP |
|real estate broker |veterinarian |conference planner |systems designer |
|chef |flight attendant |speech pathologist |venture capitalist |
|land developer |floral designer |HR development trainer |actor |
|physical therapist |real estate agent |ombudsman |journalist |
|stock broker |child care provider |clergy |investment broker |
|news reporter |social worker |journalist |real estate agent |
|fire fighter |fundraiser |newscaster |real estate developer |
|promoter |athletic coach |career counselor |strategic planner |
|entrepreneur |musician |housing director |political manager |
|pilot |secretary |character actor |politician |
|budget analyst |receptionist |marketing consultant |special projects developer |
|insurance agent |special events producer |musician/composer |literary agent |
|management consultant |teacher: preschool |artist |restaurant/bar owner |
|franchise owner |teacher: elementary |information-graphics |technical trainer |
|electrical engineer |emergency room nurse |...designer |diversity manager |
|aircraft mechanic |occupational therapist |human resource manager |art director |
|technical trainer |exercise physiologist |merchandise planner |personnel systems developer |
|EEG technologist |team trainer |advertising account manager |computer analyst |
|radiological technician |travel sales |dietitian/nutritionist |logistics consultant |
|emergency medical tech. |public relations specialist |speech pathologist |outplacement consultant |
|corrections officer |waiter/waitress |massage therapist |advertising creative director |
|flight attendant |labor relations mediator |editor/art director |radio/TV talk show host |
|ESTJ |ESFJ |ENFJ |ENTJ |
|government employee |nurse |entertainer |program designer |
|pharmaceutical sales |social worker |recruiter |attorney |
|auditor |caterer |artist |administrator |
|computer analyst |flight attendant |newscaster |office manager |
|technical trainer |bookkeeper |writer/journalist |chemical engineer |
|project manager |medical/dental assistant |recreation director |sales manager |
|officer manager |exercise physiologist |librarian |logistics consultant |
|factory supervisor |elementary school teacher |facilitator |franchise owner |
|credit analyst |minister/priest/rabbi |politician |new business developer |
|electrical engineer |retail owner |psychologist |personnel manager |
|stockbroker |officer manager |housing director |investment banker |
|regulatory compliance |telemarketer |career counselor |labor relations |
|...officer |counselor |sales trainer |management trainer |
|chief information officer |special education teacher |travel agent |credit investigator |
|construction worker |merchandise planner |program designer |mortgage broker |
|general contractor |credit counselor |corporate/team trainer |corporate team trainer |
|paralegal |athletic coach |child welfare worker |environmental engineer |
|industrial engineer |insurance agent |social worker (elderly |biomedical engineer |
|budget analyst |sales representative |...services) |business consultant |
|data base manager |massage therapist |interpreter/translator |educational consultant |
|funeral director |medical secretary |occupational therapist |personal financial planner |
|cook |child care provider |executive: small business |network integration |
|security guard |bilingual education teacher |alcohol/drug counselor |...specialist |
|dentist |professional volunteer |sales manager |media planner/buyer |
| |careerwebmaster@ios. |
| |U.S. Department of the Interior |
| |Revised: Monday, 06-Nov-2000 09:42:48 EST |
| |(Source Web Site: ) |
Partial Lists of Introvert Reinforcer Careers and Jobs from the US Department of the Interior (DOI) Web Site
|ISTJ |ISFJ |INFJ |INTJ |
|management |counseling |career counselor |management consultant |
|accounting |ministry |psychologist |economist |
|auditing |library work |educational consultant |scientist |
|efficiency expert |nursing |special education teacher |computer programmer |
|engineer |secretarial |librarian |environmental planner |
|geologist |curators |artist |new business developer |
|bank examiners |bookkeepers |playwright |curriculum designer |
|organization development |dental hygienists |novelist/poet |administrator |
|electricians |computer operator |editor/art director |mathematician |
|dentists |personnel administrator |information-graphics |psychologist |
|pharmacist |paralegal |...designer |neurologist |
|school principals |real estate agent |HRM manager |biomedical researcher |
|school bus drivers |artist |merchandise planner |strategic planner |
|file clerk |interior decorator |environmental lawyer |civil engineer |
|stock broker |retail owner |marketer |intellectual properties attorney |
|legal secretary |musician |job analyst |designer |
|computer operator |elementary school teacher |mental health counselor |editor/art director |
|computer programmer |physical therapist |dietitian/nutritionist |inventor |
|technical writer |nurse |research |informational-graphics |
|chief information officer |social worker |educational consultant |...designer |
|police officer |personnel counselor |architects |financial planner |
|real estate agent |alcohol/drug counselor |interpreter/translator |judge |
|ISTP |ISFP |INFP |INTP |
|surveyor |bookkeeper |information-graphics |strategic planning |
|fire fighter |clerical supervisor |...designer |writer |
|private investigator |dental assistant |college professor |staff development |
|pilot |physical therapist |researcher |lawyer |
|police officer |mechanic |legal mediator |architect |
|purchasing agent |radiology technologist |social worker |software designer |
|chiropractor |surveyor |holistic health |financial analyst |
|medical technician |chef |...practitioner |college professor |
|securities analyst |forester |occupational therapist |photographer |
|computer repair person |geologist |diversity manager |logician |
|race car driver |landscaper designer |human resource |artist |
|computer programmer |crisis hotline operator |...development specialist |systems analyst |
|electrical engineer |teacher: elementary |employment development |neurologist |
|legal secretary |beautician |...specialist |physicist |
|coach/trainer |typist |minister/priest/rabbi |psychologist |
|commercial artist |jeweler |missionary |research/development |
|carpenter |gardener |psychologist |...specialist |
|paralegal |potter |writer: poet/novelist |computer programmer |
|dental assistant |painter |journalist |data base manager |
|radiological technician |botanist |editor/art director |chemist |
|marine biologist |marine biologist |organizational development |biologist |
|software developer |social worker |...specialist |investigator |
| |careerwebmaster@ios. |
| |U.S. Department of the Interior |
| |Revised: Monday, 06-Nov-2000 09:42:48 EST |
| |(Source Web Site: ) |
Excerpts from the Kelly Web Site[34] Describing Five Personality Typologies (PTypes) and Corresponding Crosswalks of those Five Personality Typologies
PType Personality Types
|PTypes | Anyone is free to use any part of this chart with or without credit. |Noteworthy Examples | |
|Correspondence of five personality typologies | |
|PTypes |Keirsey's/ |Riso's |PTypes |Brau's | |
|personality |Myers- |Ennea- |personality |astro- | |
|type1 |Briggs’ |gram |disorder4 |logical | |
| |type2 |type3 | |type5 | |
| | | | | | |
|Conscientious |ENFJ |1 |Obsessive-Compulsive |Aquarius | |
|Sensitive |INFJ |4+(5) |Avoidant |Pisces | |
|Vigilant |ENFP |6+(5) |Paranoid |Scorpio | |
|Dramatic |INFP |4+(3) |Histrionic |Leo | |
| | | | | | |
|Aggressive |ENTJ |8 |Sadistic |Aries | |
|Idiosyncratic |INTJ |5+(4) |Schizotypal |Aries | |
|Inventive |ENTP |3+(4) |Compensatory Narcissistic |Gemini | |
|Solitary |INTP |5+(6) |Schizoid |Gemini | |
| | | | | | |
|Leisurely |ESTJ |9+(8) |Passive-Aggressive |Taurus | |
|Serious |ISTJ |9+(1) |Depressive |Taurus | |
|Self-sacrificing |ESFJ |2 |Masochistic |Cancer | |
|Devoted |ISFJ |6+(7) |Dependent |Virgo | |
| | | | | | |
|Self-confident |ESTP |3+(2) |Narcissistic |Capricorn | |
|Adventurous |ISTP |7+(8) |Antisocial |Sagittarius | |
|Mercurial |ESFP |7+(6) |Borderline |Libra | |
|Artistic |ISFP |7+(6) |Cyclothymic |Libra | |
References[35] Cited on Kelley's Web Site for the above listed Crosswalks
Vocational Interest and Personality Reinforcer (VIPR) General Job-based Personality Types with Correspondent Crosswalks to General Jung People-based Personality Type
|ORD[36] |TYPE[37] |DESCRIPT[38] | |
|01 |ESTJ |Vocational Interest and Personality Reinforcer Type: ESTJ. Out of the 12,775 specific 9-digit DOT-Coded |
| | |Job Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 5,063 (39.63%) were |
| | |classified ESTJ. |
|01 |ESTJ |Jung-based Personality Type Correspondent: ESTJ. Out of 6,263,334 people taking the Temperament Sorter and|
| | |the Character Sorter on the Temperament Web Site, 689,423 (11.01%) were classified|
| | |ESTJ as of 12/15/2000. |
|02 |ISFP |Vocational Interest and Personality Reinforcer Type: ISFP. Out of the 12,775 specific 9-digit DOT-Coded |
| | |Job Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 3,690 (28.88%) were |
| | |classified ISFP. |
|02 |ISFP |Jung-based Personality Type Correspondent: ISFP. Out of 6,263,334 people taking the Temperament Sorter and|
| | |the Character Sorter on the Temperament Web Site, 187,154 (2.99%) were classified |
| | |ISFP as of 12/15/2000. |
|03 |ESFP |Vocational Interest and Personality Reinforcer Type: ESFP. Out of the 12,775 specific 9-digit DOT-Coded |
| | |Job Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 919 (7.19%) were classified|
| | |ESFP. |
|03 |ESFP |Jung-based Personality Type Correspondent: ESFP. Out of 6,263,334 people taking the Temperament Sorter and|
| | |the Character Sorter on the Temperament Web Site, 300,792 (4.80%) were classified |
| | |ESFP as of 12/15/2000. |
|04 |ESTP |Vocational Interest and Personality Reinforcer Type: ESTP. Out of the 12,775 specific 9-digit DOT-Coded |
| | |Job Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 541 (4.23%) were classified|
| | |ESTP. |
|04 |ESTP |Jung-based Personality Type Correspondent: ESTP. Out of 6,263,334 people taking the Temperament Sorter and|
| | |the Character Sorter on the Temperament Web Site, 169,604 (2.71%) were classified |
| | |ESTP as of 12/15/2000. |
|05 |ISTJ |Vocational Interest and Personality Reinforcer Type: ISTJ. Out of the 12,775 specific 9-digit DOT-Coded |
| | |Job Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 474 (3.71%) were classified|
| | |ISTJ. |
|05 |ISTJ |Jung-based Personality Type Correspondent: ISTJ. Out of 6,263,334 people taking the Temperament Sorter and|
| | |the Character Sorter on the Temperament Web Site, 662,915 (10.58%) were classified|
| | |ISTJ as of 12/15/2000. |
|06 |ESFJ |Vocational Interest and Personality Reinforcer Type: ESFJ. Out of the 12,775 specific 9-digit DOT-Coded |
| | |Job Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 439 (3.44%) were classified|
| | |ESFJ. |
|06 |ESFJ |Jung-based Personality Type Correspondent: ESFJ. Out of 6,263,334 people taking the Temperament Sorter and|
| | |the Character Sorter on the Temperament Web Site, 763,261 (12.19%) were classified|
| | |ESFJ as of 12/15/2000. |
|07 |ISTP |Vocational Interest and Personality Reinforcer Type: ISTP. Out of the 12,775 specific 9-digit DOT-Coded |
| | |Job Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 377 (2.95%) were classified|
| | |ISTP. |
|07 |ISTP |Jung-based Personality Type Correspondent: ISTP. Out of 6,263,334 people taking the Temperament Sorter and|
| | |the Character Sorter on the Temperament Web Site, 135,786 (2.17%) were classified |
| | |ISTP as of 12/15/2000. |
|08 |ENTJ |Vocational Interest and Personality Reinforcer Type: ENTJ. Out of the 12,775 specific 9-digit DOT-Coded |
| | |Job Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 237 (1.86%) were classified|
| | |ENTJ. |
|08 |ENTJ |Jung-based Personality Type Correspondent: ENTJ. Out of 6,263,334 people taking the Temperament Sorter and|
| | |the Character Sorter on the Temperament Web Site, 198,653 (3.17%) were classified |
| | |ENTJ as of 12/15/2000. |
Vocational Interest and Personality Reinforcer (VIPR) General Job-based Personality Types with Correspondent Crosswalks to General Jung People-based Personality Type
|ORD |TYPE |DESCRIPT | |
|09 |ISFJ |Vocational Interest and Personality Reinforcer Type: ISFJ. Out of the 12,775 specific 9-digit DOT-Coded Job |
| | |Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 235 (1.84%) were classified ISFJ. |
|09 |ISFJ |Jung-based Personality Type Correspondent: ISFJ. Out of 6,263,334 people taking the Temperament Sorter and the |
| | |Character Sorter on the Temperament Web Site, 605,759 (9.67%) were classified ISFJ as |
| | |of 12/15/2000. |
|10 |ENTP |Vocational Interest and Personality Reinforcer Type: ENTP. Out of the 12,775 specific 9-digit DOT-Coded Job |
| | |Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 215 (1.68%) were classified ENTP. |
|10 |ENTP |Jung-based Personality Type Correspondent: ENTP. Out of 6,263,334 people taking the Temperament Sorter and the |
| | |Character Sorter on the Temperament Web Site, 139,331 (2.22%) were classified ENTP as |
| | |of 12/15/2000. |
|11 |INTJ |Vocational Interest and Personality Reinforcer Type: INTJ. Out of the 12,775 specific 9-digit DOT-Coded Job |
| | |Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 173 (1.35%) were classified INTJ. |
|11 |INTJ |Jung-based Personality Type Correspondent: INTJ. Out of 6,263,334 people taking the Temperament Sorter and the |
| | |Character Sorter on the Temperament Web Site, 328,426 (5.24%) were classified INTJ as |
| | |of 12/15/2000. |
|12 |INTP |Vocational Interest and Personality Reinforcer Type: INTP. Out of the 12,775 specific 9-digit DOT-Coded Job |
| | |Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 120 (0.94%) were classified INTP. |
|12 |INTP |Jung-based Personality Type Correspondent: INTP. Out of 6,263,334 people taking the Temperament Sorter and the |
| | |Character Sorter on the Temperament Web Site, 193,629 (3.09%) were classified INTP as |
| | |of 12/15/2000. |
|13 |ENFJ |Vocational Interest and Personality Reinforcer Type: ENFJ. Out of the 12,775 specific 9-digit DOT-Coded Job |
| | |Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 91 (0.71%) were classified ENFJ. |
|13 |ENFJ |Jung-based Personality Type Correspondent: ENFJ. Out of 6,263,334 people taking the Temperament Sorter and the |
| | |Character Sorter on the Temperament Web Site, 465,565 (7.43%) were classified ENFJ as |
| | |of 12/15/2000. |
|14 |INFP |Vocational Interest and Personality Reinforcer Type: INFP. Out of the 12,775 specific 9-digit DOT-Coded Job |
| | |Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 90 (0.70%) were classified INFP. |
|14 |INFP |Jung-based Personality Type Correspondent: INFP. Out of 6,263,334 people taking the Temperament Sorter and the |
| | |Character Sorter on the Temperament Web Site, 426,896 (6.82%) were classified INFP as |
| | |of 12/15/2000. |
|15 |ENFP |Vocational Interest and Personality Reinforcer Type: ENFP. Out of the 12,775 specific 9-digit DOT-Coded Job |
| | |Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 70 (0.55%) were classified ENFP. |
|15 |ENFP |Jung-based Personality Type Correspondent: ENFP. Out of 6,263,334 people taking the Temperament Sorter and the |
| | |Character Sorter on the Temperament Web Site, 538,008 (8.59%) were classified ENFP as |
| | |of 12/15/2000. |
|16 |INFJ |Vocational Interest and Personality Reinforcer Type: INFJ. Out of the 12,775 specific 9-digit DOT-Coded Job |
| | |Types in the MVQS2001 McDOT 5th Edition Dictionary of Occupational Titles, 40 (0.31%) were classified INFJ. |
|16 |INFJ |Jung-based Personality Type Correspondent: INFJ. Out of 6,263,334 people taking the Temperament Sorter and the |
| | |Character Sorter on the Temperament Web Site, 458,132 (7.31%) were classified INFJ as |
| | |of 12/15/2000. |
Methodology
To accomplish the purposes of this study required the reduction of 16 sets of General Careers and Job Type lists to 16 Most Appropriate, Independent, Mutually Exclusive, sets of Specific Vocational Interest and Personality Reinforcer (VIPR) Job Types
The 16 DOI lists referred to General sets of Careers and Jobs (around 21 or 22 per list). They were non-specific and contained duplicate Careers and Jobs listings within and across the 16 lists. Since duplicates were unclassifiable to a single, most appropriate, Specific Vocational Interest and Personality Reinforcer (VIPR) Job Type Lists, they were eliminated. This left 11-12 non-duplicated General sets of Careers and Jobs.
Eliminating duplicate Careers and Jobs from the 16 General Careers and Jobs lists transformed them into 16 Tip of the Iceberg lists of Careers and Jobs Clusters. These Tip of the Iceberg lists were reviewed for purposes of identifying the 16 most reasonable center-of-the-cluster, mutually exclusive sets of Specific 9-digit McDOT Coded VIPR Job Types (N=23 - 43). These sets were required to re-expand each list to include up to 35 Specific VIPR Job Types with very high Transferable Skills (TS level 97) Valences.
These 16 very high TS Valence VIPR lists were then processed through MTSP using the MTSP2000 Transferable Skills (TS) Algorithm (Grimley, Williams, Hahn, & Dennis, 2000). The purpose was to establish and rank order all possible Specific VIPR Job Type lists (N=12,775 each) in descending order by TS Valence by VQ1 by SVP1 and in ascending order by McDOT Code, for the 16 lists. The final sort for Vocational Interest and Personality Reinforcer (VIPR) Job-based Personality Types was completed prior to the removal of duplicates to reduce the 16 VIPR Sets of Job Types to a final N of 12,775 Specific Job Types, across the 16 Independent, Mutually Exclusive, VIPR Job Types.
Put another way, after removal of initially identified duplicates, all Specific jobs were duplicated 16 times each, with variable Transferable Skills (TS) Valence levels, relative to each of the 16 VIPR Sets of Job Types. Then, the final 16, most appropriate Vocational Interest and Personality Reinforcer (VIPR) lists of Job Types were constructed by retaining only those Specific Job Types with the highest possible TS Valence across each set of 16 job duplicates. After eliminating the 15 other jobs with duplicate or lesser TS Valences across the 16 VIPR lists, the goal of establishing the final 16 most appropriate, seemingly independent & mutually exclusive, VIPR lists of Job Types was accomplished.
Design and Development of the MVQS VIPR Job-based Type Indicator: A Criterion-Referenced, Paired Associates Jobs Typology Instrument
In designing the MVQS VIPR Job-based Type Indicator Instrument, it was decided that 108 sets of optimally balanced, paired associate VIPR Job-based Specific Job Types would be required to assure reasonable expectations of moderate to very high Test-Retest Reliability (i.e., in the Rxx=0.80-0.99 range).
Therefore, from each of the final 16 VIPR Job-based Personality Type Lists, 13-16 Specific Job Types with TS Valences of 97 were selected for inclusion in the MVQS VIPR Job-based Type Indicator sets of optimally balanced, paired associates (N=213).
The final N of 108 sets of optimally balanced, paired associates required that three additional Specific VIPR Job Types from the VIPR INFJ Set of Job Types, with slightly lower TS Valences (two with TS Valences of 94 and one with a TS Valance of 91), be incorporated. The addition of these three Specific VIPR INFJ Job Types completed the list of 216 Specific VIPR Job Types (selected across all 16 VIPR Job Types lists) required to finalize the 108 sets of optimally balanced, paired associates for the MVQS VIPR Job-based Personality Type Indicator.
Following the development of 108 sets of optimally balanced, paired associates, the MVQS VIPR Job-based Personality Type Indicator instrument was placed in an MS Excel Spreadsheet complete with instructions and scoring formulas designed to yield an individualized, single-best VIPR Type for each person completing the MVQS VIPR Job-based Personality Type Indicator. This instrument was then sent via e-mail attachment to a number of Expert Vocational Practitioners for peer-review and field-testing.
Results
Face and Content Validity were established by Expert Vocational Practitioners to be in the very high range for the paper and pencil version of the MVQS VIPR Job-based Personality Type Indicator during the peer-review and field-testing phase.
Suggestions for improvements were solicited from Expert Vocational Practitioners completing peer-review and field-testing of the Instrument. All recommendations from Expert Vocational Practitioners completing peer-review and field-testing of the paper and pencil version of the instrument, as well as the programming format suggestions for the MVQS VIPR Job-based Personality Type Indicator instrument to be included in the MVQS2001 McPLOT Sub-Program were reviewed and considered.
The best suggestions were selected, incorporated and implemented in the final versions of both MVQS VIPR Job-based Personality Type Indicator instruments. The paper and pencil version was printed for distribution (See next 5 pages). Programming for the MVQS VIPR Job-based Personality Type Indicator instrument to be included in the MVQS2001 McPLOT Sub-Program was initiated and completed.
The MVQS VIPR Job-Based Vocational Personality Type Indicator
|MVQS Vocational Interest and Personality Reinforcer (VIPR) Type Indicator |
|(A McCroskey 5th Ed Dictionary of Occupational Titles (McDOT) Paired-Associates, Criterion-Referenced Test) |
|© 2001 by Billy J. McCroskey, Ph.D. All Rights Reserved. | | | | |
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| | NAME: | | | | DATE: | |
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|Instructions: Review each Pair of Jobs and Indicate your Preference by Placing a "1" in either the "E" or "I" box. |
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| |E TITLES |E | | |I TITLES |I |
|1 |Teacher, Industrial Arts | | |1 |Plant Pathologist | |
|2 |Production Engineer | | |2 |Botanist | |
|3 |Machinist | | |3 |Forester | |
|4 |Business-Enterprise Officer | | |4 |Supervisor, Transcribing Operators | |
|5 |Director, Labor Standards | | |5 |Jeweler | |
|6 |Teacher, Secondary School | | |6 |Jeweler Apprentice | |
|7 |Zoo Veterinarian | | |7 |Periodontist | |
|8 |Aerodynamicist | | |8 |Pediatric Dentist | |
|9 |Field-Service Engineer | | |9 |Accountant, Tax | |
|10 |Cardiopulmonary Technologist, Chief | | |10 |Electrical-Prospecting Engineer | |
|11 |Special Procedures Technologist, CT Scan | | |11 |Electrical Test Engineer | |
|12 |Radiologic Technologist | | |12 |Electrical Engineer | |
|13 |Nurse Anesthetist | | |13 |Internist | |
|14 |Teacher, Adventure Education | | |14 |Ophthalmologist | |
|15 |Speech Pathologist | | |15 |Family Practitioner | |
|16 |Biomedical Engineer | | |16 |Animal Scientist | |
|17 |Tax Attorney | | |17 |Airport Engineer | |
|18 |Lawyer | | |18 |Hydraulic Engineer | |
|19 |Electrical Engineer, Power System | | |19 |Aquatic Biologist | |
|20 |Induction-Coordination Power Engineer | | |20 |Radiopharmacist | |
|21 |Mechanical-Design Engineer, Facilities | | |21 |Statistician, Mathematical | |
|22 |Optometrist | | |22 |Illustrator, Medical and Scientific | |
|23 |Dietitian, Teaching | | |23 |Acupuncturist | |
|24 |Dietitian, Consultant | | |24 |Sociologist | |
|25 |Teacher, Art | | |25 |Occupational Therapist | |
|26 |Musician, Instrumental | | |26 |Educational Specialist | |
|27 |Manager, Advertising | | |27 |Writer, Prose, Fiction and Nonfiction | |
| |E Score: | | | |I Score: | |
| | | | | | | |
|MVQS Vocational Interest and Personality Reinforcer (VIPR) Type Indicator |
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| | | | | | | |
| | NAME: | | | | DATE: | |
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|Instructions: Review each Pair of Jobs and Indicate your Preference by Placing a "1" in either the "S" or "N" box. |
| | | | | | | |
| |S TITLES |S | | |N TITLES |N |
|1 |Documentation Engineer | | |1 |Environmental Analyst | |
|2 |Contractor | | |2 |Reliability Engineer | |
|3 |Industrial Engineer | | |3 |Computer Systems Hardware Analyst | |
|4 |Tool Planner | | |4 |Lawyer, Admiralty | |
|5 |Production Planner | | |5 |Manager, Personnel | |
|6 |Economic Development Coordinator | | |6 |Director, Industrial Relations | |
|7 |Landscape Architect | | |7 |Chemical Engineer | |
|8 |Experimental Aircraft Mechanic | | |8 |Protection Engineer | |
|9 |Supervisor, Personnel Clerks | | |9 |Illuminating Engineer | |
|10 |Veterinarian, Laboratory Animal Care | | |10 |Materials Scientist | |
|11 |Aeronautical Engineer | | |11 |Irrigation Engineer | |
|12 |Aeronautical-Design Engineer | | |12 |Sanitary Engineer | |
|13 |Radiologic Technologist, Chief | | |13 |Physicist | |
|14 |Special Procedures Technologist, Angiogram | | |14 |Electro-Optical Engineer | |
|15 |Echocardiograph Technician | | |15 |Nematologist | |
|16 |Dentist | | |16 |Home Economist | |
|17 |Quality Control Engineer | | |17 |Clergy Member | |
|18 |Management Analyst | | |18 |Dietitian, Clinical | |
|19 |Nurse Practitioner | | |19 |Psychiatrist | |
|20 |Nurse Supervisor, Evening-or-Night | | |20 |Medical Physicist | |
|21 |Nurse, School | | |21 |Hearing Officer | |
|22 |Chiropractor | | |22 |Arranger | |
|23 |Electronics Technician | | |23 |Faculty Member, College or University | |
|24 |Athletic Trainer | | |24 |Composer | |
|25 |Radiologist | | |25 |Consultant, Education | |
|26 |Pediatrician | | |26 |Broker-and-Market Operator, Grain | |
|27 |Proctologist | | |27 |Industrial Therapist | |
| |S Score: | | | |N Score: | |
| | | | | | | |
|MVQS Vocational Interest and Personality Reinforcer (VIPR) Type Indicator |
| | | | | | | |
| | | | | | | |
| | NAME: | | | | DATE: | |
| | | | | | | |
|Instructions: Review each Pair of Jobs and Indicate your Preference by Placing a "1" in either the "T" or "F" box. |
| | | | | | | |
| |T TITLES |T | | |F TITLES |F |
|1 |Manufacturing Engineer | | |1 |Physical Therapist | |
|2 |Chef De Froid | | |2 |Painter | |
|3 |Welder Apprentice, Arc | | |3 |Landscape Gardener | |
|4 |Welder, Arc | | |4 |Automobile Mechanic | |
|5 |Machine Setter | | |5 |Bookkeeper | |
|6 |Pharmaceutical Detailer | | |6 |General-Ledger Bookkeeper | |
|7 |Magnetic Resonance Imaging (MRI) Techo | | |7 |Aeronautical Project Engineer | |
|8 |Technologist, Cardiac Catheterization | | |8 |Aeronautical-Research Engineer | |
|9 |Polysomnographic Technician | | |9 |Stress Analyst | |
|10 |Endodontist | | |10 |Nurse, Head | |
|11 |Pharmacist | | |11 |Nurse, Supervisor | |
|12 |Writer, Technical Publications | | |12 |Mohel | |
|13 |Electrolysis-and-Corrosion-Control Engineer | | |13 |Urologist | |
|14 |Automobile Racer | | |14 |Obstetrician | |
|15 |Electronics Mechanic | | |15 |Physiatrist | |
|16 |Maintainability Engineer | | |16 |Nurse, Instructor | |
|17 |Title Attorney | | |17 |Photojournalist | |
|18 |Lawyer, Criminal | | |18 |Sales-Promotion Representative | |
|19 |Electrical-Design Engineer | | |19 |Illustrator | |
|20 |Applications Engineer, Manufacturing | | |20 |Patent Agent | |
|21 |Power-Distribution Engineer | | |21 |Appeals Referee | |
|22 |Architect | | |22 |Orchestrator | |
|23 |Poultry Scientist | | |23 |Psychologist, Chief | |
|24 |Civil Engineer | | |24 |Clinical Therapist | |
|25 |Biologist | | |25 |Occupational Analyst | |
|26 |Physicist, Theoretical | | |26 |Supervisor, Education | |
|27 |Plant Engineer | | |27 |Humorist | |
| |T Score: | | | |F Score: | |
| | | | | | | |
|MVQS Vocational Interest and Personality Reinforcer (VIPR) Type Indicator |
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| | | | | | | |
| | NAME: | | | | DATE: | |
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|Instructions: Review each Pair of Jobs and Indicate your Preference by Placing a "1" in either the "J" or "P" box. |
| | | | | | | |
| |J TITLES |J | | |P TITLES |P |
|1 |Time-Study Engineer | | |1 |Printmaker | |
|2 |Factory Lay-Out Engineer | | |2 |Airframe-and-Power-Plant Mechanic | |
|3 |Real-Estate Agent | | |3 |Supervisor, Dairy Farm | |
|4 |Director, Arts-and-Humanities Council | | |4 |Assembler and Tester, Electronics | |
|5 |Director, Unemployment Insurance | | |5 |Typing Section Chief | |
|6 |Director, Consumer Affairs | | |6 |Sample Maker I | |
|7 |Public-Health Dentist | | |7 |Veterinarian | |
|8 |Manager, Quality Control | | |8 |Nurse, Private Duty | |
|9 |Manager, Records Analysis | | |9 |Fashion Designer | |
|10 |Nurse, General Duty | | |10 |Emergency Medical Technician | |
|11 |Nurse-Midwife | | |11 |Ultrasound Technologist | |
|12 |Nurse, Staff, Occupational Health Nursing | | |12 |Battalion Chief | |
|13 |Chemical-Test Engineer | | |13 |Electrical-Research Engineer | |
|14 |Director, Media Marketing | | |14 |Motorcycle Racer | |
|15 |District Attorney | | |15 |Electronics-Mechanic Apprentice | |
|16 |Allergist-Immunologist | | |16 |Power-Transmission Engineer | |
|17 |Cardiologist | | |17 |Mechanical-Design Engineer, Products | |
|18 |Gynecologist | | |18 |Mechanical Engineer | |
|19 |Railroad Engineer | | |19 |Chemist | |
|20 |Dairy Scientist | | |20 |Chemist, Food | |
|21 |Transportation Engineer | | |21 |Statistician, Applied | |
|22 |Director of Institutional Research | | |22 |Doctor, Naturopathic | |
|23 |Community Dietitian | | |23 |Graduate Assistant | |
|24 |Social Worker, School | | |24 |Counselor, Nurses' Association | |
|25 |Job Analyst | | |25 |Planner, Program Services | |
|26 |Playwright | | |26 |Clinical Psychologist | |
|27 |Screen Writer | | |27 |Counselor | |
| |J Score: | | | |P Score: | |
| | | | | | | |
|MVQS-VIPR Type Indicator Results | | | | |
| | NAME: | | | | DATE: | |
| |(E)xtroversion Score: | | | |(I)ntroversion Score: | |
| | | | | | | |
| |(S)ensing Score: | | | |I(N)tuiting Score: | |
| | | | | | | |
| |(T)hinking Score: | | | |(F)eeling Score: | |
| | | | | | | |
| |(J)udgement Score: | | | |(P)erception Score: | |
| |MVQS-VIPR TYPE | | | | | |
| | | 81st percentile, and 4 ranges from the 42nd to the 57th percentiles). Being distracted makes it more difficult to perform well on Reasoning, Math and Language tests. The single GED variable that is expected to show the greatest drop, however, is Math or Arithmetic (written and verbal), as it requires the highest level of abstract thought of the three GED variables.
Perception (S, P and Q) variables become impaired when a person is distracted and depressed. These variables are on an ascending scale of 1 to 5 (1 < 5th percentile, 5 > 79th percentile, and 3 and 4 range from the 39th to the 79th percentiles). Diminished Clerical (Q) stemming from diminished attention to detail in written and tabular material is the single Perception variable typically expected to show the most impairment as a result of emotional trauma. Similarly, like falling dominoes, as a result of emotional trauma affecting GED and Perception Variables, Motor Coordination (K), Finger Dexterity (F), Manual Dexterity (M) and Eye-Hand-Foot Coordination (E) tend to drop measurably.
Case Study of an Emotional Trauma Client
In this example case study, the Emotional Trauma Client (TC) was a female employed in the medical field as a Registered Nurse (RN). TC was in her early 30s with a graduate degree at the time of an automotive accident that left her with scars, lifting restrictions, chronic pain (partially controlled by medication) and symptoms of posttraumatic stress disorder (including fatigue and impaired concentration). At the time of evaluation, TC had reached Maximum Medical Improvement and had returned (with significant accommodation) to her previous employment with her previous employer. TC was able to work a two to three hours per day at her previous employment prior to exhibiting a decrease in concentration and an increase in fatigue. Her workday was split between her duties as a Nurse (between two and four hours per work day) and other work tasks involving training and supportive duties that did not require medication management or strenuous physical activity. Partially due to her ongoing litigation, her employer made no change in her job description or salary following her return to work. However, it was well documented that she was not able to fulfill the essential duties of her employment. Her immediate supervisor was supportive of her efforts and position. However, he was scheduled to retire in a couple of years.
Vocational Analysis of the 10 VSV Most Affected by Emotional Trauma
Comparing TC's previous jobs and plotting the highest job demands across all of these jobs produced Table 1. Reasoning, Math and Language were above average (5) as were other ability scales (4). Her work history included a variety of job tasks that combined to produce the below listed High Across Jobs Profile on the 10 VSV most likely to be affected by Emotional Trauma, along a Vocational Quotient of 156.61 across all 24 VSV.
TABLE 1
Pre-Injury High Across Jobs Profile
|R |M |L |
|Range A |Under $6.75 |Under $14,040 |
|Range B |$6.75 to $8.49 |$14,040 to $17,659 |
|Range C |$8.50 to $9.99 |$17,660 to $20,779 |
|Range D |$10.00 to $11.24 |$20,780 to $23,399 |
|Range E |$11.25 to $13.24 |$23,400 to $27,559 |
|Range F |$13.25 to $15.74 |$27,560 to $32,759 |
|Range G |$15.75 to $19.24 |$32,760 to $40,039 |
|Range H |$19.25 to $24.24 |$40,040 to $50,439 |
|Range I |$24.25 to $43.24 |$50,440 to $89,959 |
|Range J |$43.25 to $60.00 |$89,960 to $124,820 |
|Range K |$60.01 and over |$124,821 and over |
Hourly versus annual wage reporting: For each occupation, respondents are asked to report the number of employees paid within specific wage intervals. The intervals are defined both as hourly rates and the corresponding annual rates, where the annual rates are constructed by multiplying the hourly wage rate for the interval by the typical work year of 2,080 hours. In reporting, the respondent can reference either the hourly or the annual rate, but is instructed to report the hourly rate for part-time workers.
Annual wage: Most of the annual mean wage estimates in this release are calculated by multiplying the mean wage by a year-round, full-time hours figure of 2,080 hours per year (52 weeks by 40 hours). Most employees are paid at an hourly rate by their employers and may work less than or more than 40 hours per week. Thus, the annual wage estimates may not represent the actual annual pay received by the employee. There are a small number of occupations where only an annual wage figure is provided. The workers in these occupations generally work less than the usual 2,080 hours per year. Since the survey does not collect the actual hours worked, the hourly rate cannot be calculated with a reasonable degree of confidence from the annual wages. For these occupations, therefore, only the annual salary is reported, which has been calculated directly from the data (rather than by multiplying an hourly figure by 2,080 hours). Occupations that typically have a work-year of less than 2,080 hours include musical and entertainment occupations, pilots and flight attendants, and teachers.
The Unemployment Insurance (UI) Address File is a micro-level employer file prepared quarterly by each State's Employment Security Agency and submitted to the Bureau of Labor Statistics. For 1998, the file from the second quarter of 1997 is used as a sampling frame while the fourth quarter of 1998 is used as a source of population values for employment (the second quarter of 1998 is used as a source of population employment values for New Jersey).
Industry classifications are based on the 1987 Standard Industrial Classification Manual, Office of Management and Budget, 1987. Industry is classified on the basis of the major product or activity of the establishment, as determined by total sales or receipts of the calendar year prior to classification.
Scope of the OES Survey
The survey included private establishments in SIC codes 07, 10, 12-17, 20-42, 44-65, 67, 70, 72, 73, 75, 76, 78-84, 86, 87, and 89 covering agricultural services; mining; construction; manufacturing; transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. The survey also covered private and government establishments in SIC codes 806, 821, 822, 824, and 829, the Postal Service (SIC 43), as well as all remaining state and local government establishments. Data for the Postal Service are universe counts obtained from the United States Postal Service (USPS). Federal government data are obtained from the Office of Personnel Management (OPM); these data exclude information from selected agencies.
The reference date of the 1998 survey was the week that included October 12, November 12, or December 12 of 1998. The reference date for a particular establishment in this survey is dependent on its two-digit SIC code. See below.
Reference Date Industries Surveyed
October 12 07, 15-17, 41, 46, 50-62, 67, 70, 73, 79, 84
November 12 26-28, 30, 35, 36, 40, 42, 45, 47, 48, 63-65, 75, 76, 78, 80, 81, 83, 86, 87, 89
December 12 10, 12-14, 20-25, 29, 31-34, 37-39, 44, 49, 72, 82, and state and local governments
Survey Sampling Procedures
The sampling frame for this survey was the list of establishments which reported to the state Unemployment Insurance (UI) files for the two-digit SICs listed above. For the 1998 survey, the frame's reference date was the second quarter of 1997. This frame was supplemented with a list supplying establishment information on Railroads (SIC 401).
Establishments in the universe were stratified by Metropolitan Statistical Area (MSA), three-digit SIC, and size of firm (i.e., size class). Size classes were defined as follows:
|Size class |Number of employees |
|1 |1 to 4 |
|2 |5 to 9 |
|3 |10 to 19 |
|4 |20 to 49 |
|5 |50 to 99 |
|6 |100 to 249 |
|7 |250 to 499 |
|8 |500 to 999 |
|9 |1,000 or more |
In 1996 and 1997, establishments in size classes 2 to 6 were selected based on a probability sample. The sampling weights in size class 2 were adjusted to account for the employment in size class 1. In 1998, the OES Survey began sampling establishments in size class 1; thus, establishments in all size classes are now represented in the probability sample. UI reporting units with 250 or more employees are sampled with certainty across the three year cycle of the survey. Approximately one third of these units are selected within each MSA/SIC/Size class each year. The above allocation resulted in a total initial sample size of 409,347, 408,805, and 400,405 UI reporting units or establishments for 1996, 1997, and 1998. The combined initial sample size for 1996, 1997, and 1998 is 1,206,964 UI reporting units or establishments. (Note that the combined sample size is not a simple sum of the three year's samples. Some State government establishments are included in the survey each year. In the tabulations for the combined survey these establishments are only included once, from the most recent year. Federal government units are also included in the combined tabulation.)
Method of Collection
Survey schedules were initially mailed to virtually all sampled establishments. Personal visits, however, were made to some of the larger establishments. Two additional mailings were sent to nonresponding establishments at approximately three week intervals. Telephone follow-ups and, in some cases, personal visits were made to nonrespondents considered critical to the survey because of their size.
Response
Subsequent to the close-out date for National estimates, additional data were collected by the states and used to prepare their own estimates. Consequently, the response rates in most states are higher than the response rate used to develop estimates of all-industry wage rates for each MSA.
Estimation Methodology
The OES survey samples approximately 400,000 establishments each year and, over a 3-year period, contacts approximately 1.2 million establishments. Each single-year sample represents one-third of both the certainty and non-certainty strata for the full 3-year sample plan. While estimates can be made from a single year of data, the OES survey has been designed to produce estimates using the full 3 years of data. The full 3-year sample allows the production of estimates at fine levels of geography, industry, and occupational detail, while estimates using any one year of data would be subject to a higher sampling error (due to the smaller sample size) and the limitations associated with having only 1/3 of the certainty units. Producing estimates using the 3 years of sample data provides significant sampling error reductions (particularly for small geographic areas and occupations); however, it also has some quality limitations in that it requires the adjustment of earlier years' data to the current reference period--a procedure referred to as wage updating.
The 1996 OES survey estimates, which were published in December 1997, were from the first year of the new OES wage survey and were developed using only a single year (i.e., 400,000 sample units) of data. The initial estimation methodology used a weighting-class adjustment procedure for nonrespondents and an employment benchmark at the state/industry level. Since multiple years of data were not available for the 1996 estimates, the estimation procedure did not involve wage updating.
The 1997 OES survey estimates represent the second year of OES estimates and have been developed using both the 1996 and 1997 surveys. The 1997 estimates also represent the first year of using a wage-updating methodology in developing the OES survey estimates. In addition to the wage-updating procedure, the 1997 estimates used an improved estimation methodology, utilizing a nearest neighbor imputation approach for nonrespondents and applying employment benchmarks at a detailed MSA by 3-digit industry and broad size-class level. A variant of the imputation procedure is also used to account for item nonresponse. Note: Because of the difference in estimation methods for these first 2 years of OES estimates, the data from 1997 are not strictly comparable with those published from 1996.
The 1998 OES survey estimates are developed from the full three years of the OES sample. The combined 1996, 1997, and 1998 data cover approximately 1.2 million sample units. The 1998 estimates use the wage-updating methodology introduced in 1997, which uses the over-the-year fourth-quarter wage changes from the Bureau's Employment Cost Index to adjust prior years' data before combining them with data from the current year. In addition, the 1998 estimates use the estimation methodology introduced in 1997, which uses a nearest neighbor imputation approach for nonrespondents and applies employment benchmarks at a detailed MSA by 3-digit industry and broad size class level.
The wage-updating procedure is used to adjust prior year wages to reflect increases between the previous data and current year data. For wage-updating purposes, the Bureau has used the national over-the-year wage changes from the fourth quarter of 1996 to the fourth quarter of 1997 and from the fourth quarter of 1997 to the fourth quarter of 1998 for the nine occupational divisions for which ECI estimates are available. These factors are applied to both the 1996 and 1997 survey data to update them to the fourth-quarter 1998 level before combining them with the 1998 survey data. Such a procedure assumes that each occupation's wage, as measured in the earlier years, moves according to the average movement of its occupational division and that there are no major geographic or detailed occupational differences--and this may not be the case. Research is being conducted to develop procedures that may account for differences in the rate of change at more detailed levels, than the nine ECI occupational divisions.
The hot deck (nearest neighbor) imputation procedure imputes for unit nonresponse. This type of nonresponse occurs when a unit reports no employment data. In hot decking, units in the sample are stratified into 'year/State/4-digit industry/size class' cells. Within each cell, a donor (i.e., responding unit) is selected to represent each nonrespondent under the proviso that a donor can not be selected twice. The sampling frame employment is used to match donors with nonrespondents. Once a donor and nonrespondent are matched, the occupational employment totals from the donor are copied over to the nonrespondent. In the event that a donor is not available at the 'year/State/4-digit industry/size class' cell level, the procedure advances to succeeding higher level cells until a donor is found.
Occasionally a responding establishment may provide employment information, but omit wage distribution information for selected occupations. The OES survey currently uses a variation of the mean imputation procedure to impute for item nonresponse. This type of nonresponse occurs when a unit reports the total-employment for its occupations but not the corresponding employment by wage intervals. In this procedure, units in the sample are stratified into 'year/MSA/3-digit industry/size class' cells. A wage-employment distribution is then calculated for those occupations with missing wage-employment based on the usable data in the cell. Missing wage-employment is imputed using the just calculated wage-employment distribution to prorate the total-employment of those occupations with missing wage-employment.
A separate ratio estimator is used to develop estimates of occupational employment in each wage interval. The auxiliary variable is the population value of total employment obtained from the refined Unemployment Insurance files for the 1998 reference month. Within each MSA, the estimated employment for an occupation at the reported three-digit SIC/wage interval level was calculated by multiplying the weighted employment by its ratio factor. The estimated employment for an occupation at the all-industry level was obtained by summing the occupational interval employment estimate across all industries within an MSA reporting that occupation. A further adjustment to each occupational employment total was made as described in the Reliability of the Estimates section. This adjustment did not affect the mean or median wage rates. The employment and wage data for federal government workers in each occupation were added to the survey derived data.
A mean wage and a median wage are calculated using wage data from establishments in the industries that reported employment for an occupation.
Mean wage is the estimated total wages for an occupation divided by its weighted survey employment. For the upper open-ended wage interval, a Winsorized mean procedure is used to estimate the mean wage. That is, the mean wage value for the upper open-ended wage interval is set at its lower bound ($60.01). For the other intervals, a mean wage value was calculated based on occupational wage data collected by the Office of Compensation and Working Conditions. These interval mean wage values are then attributed to all workers reported in the interval. For each occupation, total weighted wages in each interval (i.e., mean wages times weighted employment) are summed across all intervals and divided by the occupation's weighted survey employment to obtain a mean wage.
Median wage is the estimated 50th percentile of the distribution of wages; 50 percent of workers in an occupation earn wages below, and 50 percent earn wages above the median wage. The wage interval containing the median wage is located using a cumulative frequency count of employment across wage intervals. After the targeted wage interval is identified, the median wage rate is then estimated by a linear interpolation procedure
Reliability of the Estimates
The occupational wage rates in this report are estimates derived from a sample survey. Two types of errors are possible in an estimate based on a sample survey - sampling error and nonsampling error. Sampling error occurs because the observations are based on a sample, not on the entire population. Nonsampling error is due to response, nonresponse, and operational errors.
Nonsampling Errors: Estimates are subject to various response, nonresponse, and operational errors during the survey process. Sources of possible errors are data collection, response, coding, transcription, data editing, nonresponse adjustment, and estimation. These errors would also occur if a complete census was conducted under the same conditions as the sample survey. Explicit measures of their effects are not available. However, it is believed that the important response and operational errors were detected and corrected during the review and validation process.
The employment total and wage data for the occupation reflects only those industries that reported the occupation. This occurs primarily in those industries where the occupation appeared on the survey form. Since every occupation does not appear on every industry-specific form, there may be a bias in the employment and wage data for some occupations. The extent of this bias is unknown.
Another source of potential bias is the limitations placed on the size of the benchmark factors. A benchmark factor is the ratio of a known employment value to a sample-derived employment estimate. This factor is used to make a post-stratification adjustment that makes the total weighted employment estimate at the state / three-digit SIC industry / Metropolitan Statistical Area (MSA) / employment size class level match the population employment at that level. The source of the population employment data is the states' Quarterly Unemployment Insurance files for the reference period of the survey. In cases where a small sample was taken, the ratio factor can become large or small. In order to prevent an establishment from contributing either too much or not enough to an MSA's wage rate estimates, the benchmark factor was not allowed to exceed a predetermined value. The total employment count for those MSAs where the benchmark factor was limited by this ceiling will be biased to a small degree in those strata. The employment not assigned to those strata because of this ceiling was then distributed across the other MSAs in the state / three-digit industry, so that the estimated employment of the State / three-digit industry would match the known employment totals at that level.
Sampling Errors: The particular sample used in this survey is one of a large number of possible samples of the same size that could have been selected using the same sample design. For example, occupational wage rate estimates derived from the different samples will differ from one another. The deviation of a sample estimate from the average of all possible sample estimates is called the sampling error. The standard error of an estimate is a measure of the variation of estimates across all possible samples and thus is a measure of the precision with which an estimate from a particular sample approximates the average result of all possible samples.
Quality Control Measures
Quality control measures implemented in the OES survey include:
• review of the specific occupations to be collected for each industry, and those to be collected in residual categories
• creating and validating the sample frame for all states at BLS-Washington
• allocating and selecting the sample for all states at BLS-Washington
• follow up solicitations of nonrespondents (especially critical nonrespondents)
• review of survey schedules to verify the accuracy and reasonableness of the reported data
• adjustments of atypical reporting units on the data file
• validation of the nonresponse adjustment factors
• validation of the population employment and ratio factors
• standardized data processing programs and activities
Employment Estimates
Employment represents the estimate of total wage and salary employment in an occupation across the industries in which it was reported. The OES survey form sent to an establishment contains between 50 and 225 OES occupations. The number of occupations listed on a form depends on the industry classification and size class of the sampled establishments. To reduce paperwork and respondent burden, no survey form contains every OES occupation.
Wage Estimates
Wages for the OES survey are straight-time, gross pay, exclusive of premium pay. Included are base rate, cost-of-living allowances, guaranteed pay, hazardous-duty pay, incentive pay including commissions and production bonuses, and on-call pay. Excluded are back pay, jury duty pay, overtime pay, severance pay, shift differentials, nonproduction bonuses, and tuition reimbursements.
Annual Wage
Most employees are paid at an hourly rate by their employers and may work less than or more than 40 hours per week. The annual wage estimates on this website are calculated by multiplying the hourly wage estimates by a year-round, full-time hours figure of 2,080 hours per year (52 weeks by 40 hours). Thus, the annual wage estimates may not represent the actual annual pay received by the employee. There are a small number of occupations where hourly wages are not published. For these occupations the annual wages have been directly calculated from the reported survey data. The workers in these occupations are paid based on an annual amount, but generally work less than the usual 2,080 hours per year. Since the survey does not collect the actual hours worked, the hourly rate cannot be calculated with a reasonable degree of confidence from the annual wages. Occupations that typically have a work-year of less than 2,080 hours include musical and entertainment occupations, flight attendants and pilots, and teachers.
Mean Hourly Wage
The mean hourly wage is the estimated total wages for an occupation divided by its weighted survey employment.
Median Hourly Wage
The median hourly wage is the estimated 50th percentile of the distribution of wages; 50 percent of workers in an occupation earn wages below, and 50 percent earn wages above the median wage.
Relative Standard Error (RSE)
The particular sample used in this survey is one of a large number of all possible samples of the same size that could have been selected using the same sample design. Estimates derived from different samples would differ from each other.
• The variance of a survey estimate is a measure of the variation among the estimates from all possible samples.
• The standard error of a survey estimate is the square root of its variance
• The relative standard error is the ratio of the standard error to the estimate itself.
The sample estimate and its standard error allows the construction of an interval estimate with a prescribed level of confidence. The interval will include the mean value of the estimates from all possible samples. To illustrate, if all possible samples were selected, and if each of these were surveyed under essentially the same conditions, and an estimate and its estimated sampling error were calculated from each sample, then:
• Approximately 90 percent of the intervals from 1.6 standard errors below to 1.6 standard errors above the derived estimate would include the average value of the estimates from all possible samples. This interval is called a 90-percent confidence interval.
• Approximately 95 percent of the intervals from two standard errors below to two standard errors above the derived estimate would include the average value of the estimates from all possible samples. This interval is called a 95-percent confidence interval.
For example, suppose that an estimated occupational employment total is 5,000 with an associated relative standard error of two percent. Based on this data, the standard error of the estimate is 100 (= 5,000 X 0.02) and the 95-percent confidence interval for the estimate is (5,000 + 200) or (4,800 to 5,200). This confidence interval is one of many that could be constructed based on the same sample design. Approximately 95 percent of these confidence intervals would encompass the average value of the estimates from all possible samples.
Methodology
All 12,775 McDOT 2000 DOT codes were grouped into OES code groups. One regression formula was derived for each of the six 1998 data points of interest (the Mean, 10th, 25th, 50th (Median) 75th, and 90th percentiles reported by the government). The OES code groups were averaged for each whole number Vocational Quotient. The small number of mean wage estimates not provided in the OES data were derived using linear regression. Wage estimates not provided for jobs with incomes larger than $60.00 per hour were likewise extrapolated using straight-line regression incorporating available OES wage estimates. For the final analysis, there were no missing wage estimates.
Each regression formula predicted the average wage for each of the six OES code group data points for each whole number Vocational Quotient (N=88). Therefore, each percentile distribution represented a different study. Since the goal of this research was to predict to the middle of each distribution, outliers (wages beyond two standard deviations from the mean) were removed using standard outlier removal analyses in each study.
Results
Initial VQ-Wage Data (Tables 1-15) and Final VQ-OES Wage Data (Tables 16-33) results are tabled and graphed below.
Initial Results: Tables 1-15 (No Outliers Removed)
|Table 1: Raw Data Inputs For Descriptive Statistics (vqhn88.sta): No Outliers Removed | |
| |VQ1 |HMEAN |WPCT10 |WPCT25 |HMEDIAN |WPCT75 |WPCT90 | |
|1 |68 |9.73 |6.1 |7.225 |9.1 |11.245 |14.25 | |
|2 |70 |9.2136 |5.89 |6.8445 |8.4009 |10.4173 |13.4773 | |
|3 |71 |10.1758 |6.1875 |7.4117 |9.3583 |11.8875 |15.4567 | |
|4 |72 |9.6165 |6.0081 |7.0486 |8.7651 |11.0198 |14.3572 | |
|5 |73 |9.7253 |5.9693 |6.9777 |8.785 |11.243 |14.9907 | |
|6 |74 |9.7012 |6.0158 |7.0714 |8.8378 |11.1974 |14.6823 | |
|7 |75 |9.7267 |6.0228 |7.1029 |8.8715 |11.2115 |14.6391 | |
|8 |76 |10.0996 |6.177 |7.3737 |9.2536 |11.7497 |15.2629 | |
|9 |77 |9.8701 |6.131 |7.2433 |9.0611 |11.4777 |14.8331 | |
|10 |78 |10.0346 |6.1617 |7.3264 |9.1961 |11.6958 |15.159 | |
|11 |79 |10.1153 |6.2326 |7.4305 |9.3165 |11.8127 |15.1396 | |
|12 |80 |10.3125 |6.309 |7.5462 |9.4924 |12.062 |15.5826 | |
|13 |81 |10.412 |6.3366 |7.6237 |9.5887 |12.221 |15.7806 | |
|14 |82 |10.6157 |6.4363 |7.7825 |9.7753 |12.4872 |16.053 | |
|15 |83 |10.6261 |6.437 |7.7784 |9.7794 |12.5174 |16.1456 | |
|16 |84 |10.7048 |6.4429 |7.8037 |9.8588 |12.6369 |16.2885 | |
|17 |85 |10.6504 |6.434 |7.7884 |9.8195 |12.5368 |16.1243 | |
|18 |86 |10.6184 |6.4341 |7.7916 |9.8138 |12.5073 |16.0178 | |
|19 |87 |10.7278 |6.472 |7.8298 |9.8723 |12.6535 |16.3139 | |
|20 |88 |10.8312 |6.5501 |7.9226 |9.9896 |12.7547 |16.3724 | |
|21 |89 |10.7139 |6.5283 |7.9041 |9.9182 |12.6003 |16.1303 | |
|22 |90 |10.8296 |6.5488 |7.9464 |10.0261 |12.7798 |16.3418 | |
|23 |91 |10.8929 |6.5663 |7.9678 |10.0628 |12.8765 |16.493 | |
|24 |92 |11.3422 |6.7205 |8.2668 |10.4803 |13.5009 |17.2667 | |
|25 |93 |11.0943 |6.668 |8.1141 |10.2426 |13.1578 |16.8283 | |
|26 |94 |10.9059 |6.7375 |8.0999 |10.1439 |12.9004 |16.309 | |
|27 |95 |11.5393 |6.9519 |8.5043 |10.7343 |13.7185 |17.3213 | |
|28 |96 |11.8409 |7.0502 |8.735 |11.0258 |14.1364 |17.9488 | |
|29 |97 |11.991 |7.1098 |8.7741 |11.1406 |14.3294 |18.2302 | |
|30 |98 |11.8345 |7.0438 |8.6603 |10.9845 |14.0585 |17.9407 | |
|31 |99 |11.9257 |7.0509 |8.6963 |11.0405 |14.2635 |18.2101 | |
|32 |100 |12.1313 |7.2131 |8.9128 |11.3045 |14.451 |18.3139 | |
|33 |101 |12.4593 |7.3283 |9.0539 |11.566 |15.0011 |19.4077 | |
|34 |102 |12.802 |7.544 |9.3582 |11.8902 |15.3347 |19.8597 | |
|35 |103 |13.5012 |7.8776 |9.8631 |12.5727 |16.2175 |20.9602 | |
|36 |104 |13.8515 |7.9063 |9.9628 |12.8569 |16.8351 |22.1937 | |
|37 |105 |15.1152 |8.3217 |10.6398 |13.8983 |18.4558 |25.0224 | |
|38 |106 |14.9219 |8.3597 |10.6903 |13.9624 |18.3069 |23.9848 | |
|39 |107 |15.2356 |8.5077 |10.832 |14.1515 |18.7268 |24.8185 | |
|40 |108 |16.4957 |9.034 |11.5769 |15.2209 |20.3391 |27.8359 | |
|41 |109 |17.1877 |9.2028 |11.9097 |15.8378 |21.5053 |29.5336 | |
|42 |110 |17.8079 |9.4559 |12.2975 |16.4381 |22.2815 |30.8589 | |
|43 |111 |17.0608 |9.2828 |11.9776 |15.8358 |21.2156 |28.6204 | |
|44 |112 |17.7987 |9.7114 |12.5156 |16.5898 |22.3348 |30.4912 | |
|45 |113 |17.3508 |9.4748 |12.2229 |16.1105 |21.4409 |29.5455 | |
|46 |114 |18.1909 |9.958 |12.8837 |17.0316 |22.8715 |30.9717 | |
|47 |115 |18.1465 |9.7334 |12.64 |16.9008 |22.958 |31.3403 | |
|48 |116 |17.925 |9.74 |12.5646 |16.6605 |22.3463 |30.8436 | |
|49 |117 |17.9615 |9.8531 |12.6848 |16.8014 |22.5428 |30.2833 | |
|50 |118 |17.5842 |9.7227 |12.4955 |16.4916 |21.9655 |29.6067 | |
|51 |119 |18.5207 |10.1664 |13.1481 |17.3923 |23.1641 |31.5677 | |
|52 |120 |19.5909 |10.4901 |13.6225 |18.3658 |25.1944 |34.2459 | |
|53 |121 |19.0001 |10.4703 |13.5323 |17.8094 |24.0781 |32.26 | |
|54 |122 |18.9973 |10.4073 |13.411 |17.7865 |23.9495 |32.1453 | |
|55 |123 |19.545 |10.7323 |13.9023 |18.5622 |24.9141 |33.2764 | |
|56 |124 |18.3497 |10.4021 |13.2547 |17.3597 |22.9063 |30.2852 | |
|57 |125 |20.3958 |11.084 |14.4751 |19.37 |26.2007 |34.267 | |
|58 |126 |20.164 |11.1314 |14.2407 |18.805 |25.4102 |34.1633 | |
|59 |127 |21.2247 |11.1828 |14.4375 |20.0333 |28.2503 |38.2089 | |
|60 |128 |21.3318 |12.4024 |15.6669 |20.4704 |27.1085 |35.3922 | |
|61 |129 |21.4662 |11.2693 |14.5533 |20.3433 |28.0948 |38.086 | |
|62 |130 |21.7976 |12.3994 |15.7652 |20.7191 |28.1891 |37.0888 | |
|63 |131 |22.1807 |13.05 |16.32 |21.4624 |29.0184 |37.1569 | |
|64 |132 |23.2925 |13.6275 |17.2334 |22.8166 |30.4753 |37.7884 | |
|65 |133 |24.2717 |13.9114 |17.9172 |24.0548 |31.9603 |41.1634 | |
|66 |134 |25.8587 |15.2353 |19.7916 |26.2559 |35.1825 |43.9406 | |
|67 |135 |24.3427 |13.5762 |17.5062 |23.8762 |32.6654 |42.7335 | |
|68 |136 |23.619 |13.0034 |16.711 |23.0603 |32.0128 |41.8569 | |
|69 |137 |22.0263 |12.7374 |16.0421 |20.8689 |28.4632 |36.8853 | |
|70 |138 |25.36 |15.482 |19.411 |25.131 |33.199 |41.415 | |
|71 |139 |24.1246 |13.9915 |17.7508 |23.2031 |31.5362 |40.9031 | |
|72 |140 |26.74 |16.4962 |20.3125 |26.035 |35.9763 |44.095 | |
|73 |141 |26.7591 |16.0273 |20.0045 |25.8445 |35.73 |44.8982 | |
|74 |142 |24.4583 |14.1867 |18.315 |23.84 |32.52 |40.4633 | |
|75 |143 |22.27 |12.41 |15.8933 |20.9667 |29.0667 |38.97 | |
|76 |144 |22.766 |13.016 |16.74 |22.05 |30.076 |37.816 | |
|77 |145 |24.8933 |13.2033 |16.81 |22.2767 |33.4 |46.8433 | |
|78 |146 |27.9075 |16.865 |21.265 |27.7175 |37.42 |45.5975 | |
|79 |147 |32.6833 |15.2467 |26.8233 |39.19 |55.28 |71.96 | |
|80 |148 |29.2133 |17.8667 |21.8467 |27.76 |38.91 |51.1433 | |
|81 |149 |39.766 |18.896 |33.694 |50.89 |68.62 |86.142 | |
|82 |150 |47.5 |19.9367 |41.7267 |66.1267 |88.7867 |111.8833 | |
|83 |151 |46.26 |20.646 |38.404 |60.86 |80.184 |100.294 | |
|84 |152 |39.1633 |18.0633 |32.0733 |49.2833 |66.48 |83.5433 | |
|85 |153 |43.9033 |19.2717 |37.2517 |58.0917 |78.5 |99.345 | |
|86 |154 |49.05 |19.05 |45.88 |72.71 |99.54 |126.37 | |
|87 |155 |47.8875 |19.715 |42.765 |67.7725 |91.475 |115.505 | |
|88 |156 |46.1517 |18.6717 |42.0217 |65.8083 |90.1217 |114.7533 | |
| | | | | | | | | |
|Table 2: Descriptive Statistics Results-All Variables: No Outliers Removed from vqhn88.sta | |
|Descriptive Statistics (vqhn88.sta) | | | | | | |
| | | | | | |Standard | | |
| |Valid N |Mean |Minimum |Maximum |Std.Dev. |Error |Skewness | |
|VQ1 |88 |112.4886 |68 |156 |25.56713 |2.725465 |-0.00272 | |
|HMEAN |88 |19.14521 |9.2136 |49.05 |10.04983 |1.071316 |1.509612 | |
|WPCT10 |88 |10.38945 |5.89 |20.646 |4.198199 |0.447529 |0.863975 | |
|WPCT25 |88 |14.50219 |6.8445 |45.88 |9.061727 |0.965983 |1.979139 | |
|HMEDIAN |88 |19.88438 |8.4009 |72.71 |14.69945 |1.566966 |2.243501 | |
|WPCT75 |88 |26.64598 |10.4173 |99.54 |20.15005 |2.148002 |2.179085 | |
|WPCT90 |88 |34.4874 |13.4773 |126.37 |25.3532 |2.70266 |2.129078 | |
| | | | | | | | | |
|Table 3: Correlation Results for all Variables: No Outliers Removed from vqhn88.sta | |
|Correlations (vqhn88.sta) | | | | | | |
|Red Marked correlations are significant at p < .05000 | | | | |
|N=88 (Casewise deletion of missing data) | | | | | |
| | | | | | | | | |
| |VQ1 |HMEAN |WPCT10 |WPCT25 |HMEDIAN |WPCT75 |WPCT90 | |
|VQ1 |1 |0.881048 |0.938424 |0.821285 |0.780183 |0.792332 |0.800457 | |
|HMEAN |0.881048 |1 |0.96484 |0.991111 |0.97976 |0.983001 |0.984092 | |
|WPCT10 |0.938424 |0.96484 |1 |0.930783 |0.899275 |0.905291 |0.905269 | |
|WPCT25 |0.821285 |0.991111 |0.930783 |1 |0.996533 |0.997419 |0.99586 | |
|HMEDIAN |0.780183 |0.97976 |0.899275 |0.996533 |1 |0.99939 |0.997568 | |
|WPCT75 |0.792332 |0.983001 |0.905291 |0.997419 |0.99939 |1 |0.999103 | |
|WPCT90 |0.800457 |0.984092 |0.905269 |0.99586 |0.997568 |0.999103 |1 | |
| | | | | | | | | |
|Table 4: Regression Results for HMEAN: No Outliers Removed from vqhn88.sta | | |
|Regression Summary for Dependent Variable: HMEAN (vqhn88.sta) | | | |
|R= .88104822 R²= .77624597 Adjusted R²= .77364418 | | | | |
|F(1,86)=298.35 p ................
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