Master of Clinical Bio-Science Program



Master of Clinical Bio-Science Program

Biostatistics I with SPSS

Instructor: Ayumi K. Shintani, Ph.D., M.P.H.

Date: November 27 – December 22, 2006

Time: Everyday 1:30PM – 4:30 PM

Course Objectives:

1. Understand the fundamental biostatistical concepts.

2. Able to appropriately format research data for statistical analysis.

3. Able to create effective graphics summarizing numerical data.

4. Able to analyze and present data from a typical clinical research project using popularly used (non-regression base) univariate / bivariate methods.

5. Know when to properly use, and be able to define most commonly used (non-regression base) inferential statistical methods.

6. Understand an introduction of a simple linear regression.

7. Understand an introduction of survival analysis.

8. Understand a concept of confounder and effect modifier in data analyses.

9. Master the statistical software package SPSS.

10. Understand the concept of sample size and power calculation and master how to perform simple sample size and power computation.

11. Able to critically interpret the statistical aspects of the medical literature.

Text Books:

Main text books:

(1) Bernard Rosner. Fundamentals of Biostatistics, Sixth Edition, Duxburry Press, ISBN: 0534418201. List Price (USD) $119.95

(2) Kirkwood BR, Sterne JAC. Essentials of Medical Statistics. $49.95. Blackwell Sciences, 2nd ed. (2001). ISBN: 0865428719.

Supplemental text books:

(1) SPSS 13.0 Advanced statistical Procedures Companion. Marija J. Norusis ISBN 0-13-186540-4

(2) SPSS 13.0 Guide to Data Analysis, Marija J. Norusis ISBN 0-13-186535-8

(3) 医学的研究のデザイン―研究の質を高める疫学的アプローチ

(4) 生物統計学入門―ハーバード大学講義テキスト    

Hardware: Students are advised to bring a laptop to all sessions.

Software:

Required:

1. SPSS software version 13 (or latest)

2. PS sample size software. Free download from:

Recommended:

3. R – statistical software. Free download from:

4. nQuery Advisor 4.0

Examination and Grading:

Homework 70%

Final Exam 30%

Course organization (subject to change):

50 min. Homework Presentation

10 min. Break

50 min. Lectures + SPSS tutorials

10 min. Break

60 min. Lectures + SPSS tutorials

Course Schedule (1st week):

|Week 1 | |Book Chapters |

|Day 1 |Introduction of the course. | |

| |Part 1. What is Biostatistics | |

| |Part 2. Statistical software / Data Entry / Data cleaning in SPSS | |

| |Lecture notes: Chapter 1 | |

|Day 2 |Types of data: Categorical, continuous, failure-time, ranks, ratios, proportions, scores, scales |Rosner 2 |

| |Summarizing data (descriptive statistics): Frequency Distributions, Percentiles, Mean, Median, Variance, Standard|Kirkwood Sterne 2 |

| |Deviation, Range, Inter-Quartile Range |Kirkwood Sterne 4 |

| |Part 3. Checking Normality | |

| |Lecture notes: Chapter 2 | |

|Day 3 |Graphical display of data (Part 1): Categorical data – histogram, Pie charts, Continuous data – histograms, |Rosner 2 |

| |stem-&-leaf plots, Box-plots, Error-bar charts, Error-bar charts with lines |SPSS Data Analysis |

| |Lecture notes: Chapter 3 |Chapter 7 |

| | |Kirkwood Sterne 3 |

|Day 4 |Graphical display of data (Part 2): Simple Scatter plot, Scatter plot matrix, Scatter plot with Lowess smoothers |SPSS |

| | |Data Analysis |

| |Lecture notes: Chapter 3 |Chapter 9 |

| | |Kirkwood Sterne 3 |

|Day 5 |Basic probability concepts: |Rosner 3 |

| |Random Experiments, Operations on Events, Multiplicative Rule of Probability, Additive Rule of Probability, | |

| |Conditional Probability, Screening, Bayes’ Rule, Bayesian Inference, Receiver Operating Characteristic (ROC) | |

| |Curves | |

| |Lecture notes: Chapter 4 | |

|Week 2 | | |

|Day 6 |Probability distributions: |Rosner 4,5 |

| |Discrete distribution, Normal distribution |Kirkwood Sterne 5 |

| |Lecture notes: Chapter 5 | |

|Day 7 |Sampling Distribution and Confidence Intervals: |Rosner 6 |

| |Computer Generating Random Numbers |Kirkwood Sterne 4, 6 |

| |Estimating Population mean | |

| |Confidence Intervals for mean and proportion | |

| |Lecture notes: Chapter 6 | |

|Day 8 |Hypothesis testing: |Rosner 7 |

| |Null and alternative hypotheses, Type 1 error, Type 2 error, Power, Sample size estimation |Kirkwood Sterne 35 |

| |Using p-value and confidence intervals |Kirkwood Sterne 8 |

| |Lecture notes: Chapter 7 | |

|Day 9 |Comparing 1 mean: Single sample t-test, Paired t-test |Rosner 8 |

| |Comparing 2 means: Student’s t-test |Kirkwood Sterne 7 |

| |Lecture notes: Chapter 8 | |

|Day 10 |Non parametric tests: |Rosner 9 |

| |Comparing 1 mean: Sign test, Wilcoxon Signed Rank test |Kirkwood Sterne 30 |

| |Comparing 2 means: Mann-Whitney U test | |

| |Lecture notes: Chapter 9 | |

Course Schedule (2nd week):

|Week 3 | | |

|Day 11 |One-way Analysis of Variance (ANOVA): Comparing 3+means |Rosner 12 |

| |Parametric method / One-way Analysis of Variances |Kirkwood Sterne 9 |

| |　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　Bonferroni correction | |

| |Non-parametric method / Kruskal Wallis tests | |

| |Lecture notes: Chapter 10 | |

|Day 12 |2 way ANOVA |Rosner 12 |

| |Concept of effect modification using means |Kirkwood Sterne 9 |

| |Lecture notes: Chapter 11 | |

|Day 13 |Introduction to a Simple Linear Regression |Rosner 11 |

| |Lecture notes: Chapter 12 |Kirkwood Sterne 10, 12 |

|Day 14 |Pearson Correlation / Spearman Correlation |Rosner 11 |

| |Lecture notes: Chapter 13 |Kirkwood Sterne 10 |

|Day 15 |Relation between Student’s t-test, one-way ANOVA, two-way ANOVA with linear regressions |Rosner 11 |

| |Lecture notes: Chapter 14 |Kirkwood Sterne 11 |

|Week 4 | | |

|Day 16 |Comparing Two proportions |Rosner 10 |

| |Measures of Association in 2 x 2 tables |Kirkwood Sterne 14, 15, 16, 17 |

| |Relative risk, Odds ratio | |

| |Test for association: Chi-squares / fisher’s exact test | |

| |Lecture notes: Chapter 15 | |

|Day 17 |Comparing 3 + proportions: |Rosner 10 |

| |Test for association for R x C tables |Kirkwood Sterne 17, 21, 36 |

| |Chi-squares test for linear trend | |

| |Comparing Correlated Categorical variables | |

| |McNemar’s Chi-square tests in matched case-control studies | |

| |Kappa statistics | |

| |Lecture notes: Chapter 16 | |

|Day 18 |Multiple 2 x 2 tables: |Rosner 10 |

| |Confounding, Effect modification, Testing for homogeneity of odds ratios, Mantel-Haenszel tests |Kirkwood Sterne 18 |

| |Lecture notes: Chapter 17 | |

|Day 19 |Survival Analysis: Kaplan-Meier estimates, Log-rank test |Rosner 14 |

| |Lecture notes: Chapter 18 |Kirkwood Sterne 26 |

|Day 20 |Final Exam | |

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