Directed Reading in Statistics, Fall Quarter, 2002



HRP 258: Introduction to Probability and Statistics for Clinical Research

Spring Quarter 2012

Class Schedule: Wed. 12:00-3:00pm, LKSC 203/4

Class Website: stanford.edu/~kcobb/courses/hrp258

Instructor Information:

Kristin Sainani

kcobb@stanford.edu

stanford.edu/~kcobb/

T211 HRP Redwood Building

TA Information:

|Michael Hurley |Antonia Valenzuela Vergara antoniav@stanford.edu |

|mphurley@stanford.edu | |

Class Objectives:

This course will equip students with the tools needed to understand and critically evaluate the medical literature. 

Specific topics to include: 1. describing data (types of data, data visualization, descriptive statistics), 2. statistical inference (probability, probability distributions, the Central Limit Theorem, sampling theory, hypothesis testing, confidence intervals, pitfalls of hypothesis testing), and 3. specific statistical tests (ttest, ANOVA, linear correlation, linear regression, non-parametric tests, relative risks, Chi-square, logistic regression, survival analysis; how to choose the right statistical test). Emphasis is on interpretation rather than analysis.

For students interested in a more math-intensive course or who want to learn SAS (statistical analysis program), they may opt to take HRP 259 (in the fall) instead of HRP 258.

Required Textbook:

What is a p-value anyway? By Andrew Vickers

Grading:

Class Participation*.………………………………………………………..……..….…....20%

Journal article review sheets………………………………………………………………10%

Homework………………….…………………………………… …..…..…………….….30%

Final Exam…………………………………………………….…………..…….……....…40%

Journal article reviews:

We will be discussing a journal article at the beginning or end of each class. Everyone should fill out a “journal article review sheet” for the article (worth 1 point each). I will also pick three or four students to read the article more carefully and be the “discussion leaders” for the week. Everyone will take one turn at this, and it will be counted as part of the class participation grade.

*Your class participation grade will be based on your contribution to these class discussions (and other in-class exercises) as well as your preparation when it is your turn to be a “discussion leader.”

Homework:

Homework for each session will include a small assignment, as well as textbook and journal article reading. Keeping up with the textbook, article, and journal article reading is essential.

Please email completed homework and journal article review sheet to hrp258@ by the beginning of class each Wednesday.

Final Exam: Final Exam will be a multiple-choice exam on the last day of class.

Class Outline (subject to modification!)

|April |Wednesday |

| |Describing Data |

|4 |Introduction to statistics: types of data; displaying data; mean, median, standard deviation; misleading graphics; misleading |

| |statistics. |

| |Reading: Chapters 1-6 Vickers |

| |Statistical Theory |

|11 |Introduction to probability and probability distributions |

| |Reading: Chapters 7-9 Vickers |

|18 |The Normal Distribution |

| |Reading: Chapters 10-15 Vickers |

|25 |Statistical Inference I: CLT; p-values, confidence intervals; statistics for one-sample and two-sample means and proportions |

| |Reading: articles: Putting P-values in Perspective; Making Sense of Confidence Intervals (on Coursework) |

| |Reading: Chapters 16-17 Vickers |

|May | |

|2 |Statistical Inference II: Statistical power; Type I and Type II error; Pitfalls of hypothesis testing |

| |Reading: articles: The Problem of Multiple Testing; Misleading Comparisons: The Fallacy of Comparing Statistical Significance (on|

| |Coursework) |

| |Reading: Chapters 22-29 Vickers |

| |Specific Statistical Tests |

|9 |Overview of statistical tests: choosing the right statistical tests; correlated and sparse data |

| |Reading: article: Accounting for Correlated Data (on Coursework) |

| |Reading: Chapters 30-34 Vickers |

|16 |Statistical Tests for Continuous Outcomes: Linear models (ttest, ANOVA, linear correlation, linear regression); non-parametric |

| |tests (Wilcoxon sign-rank, Wilcoxon sum-rank); introduction to regression modeling |

| |Reading, article: The Limitations of Statistical Adjustment (on Coursework) |

| |Reading: 18-21 Vickers |

|23 |Statistical Tests for Categorical and Binary Outcomes: Relative risks, odds ratios, Chi-square test, logistic regression; |

| |diagnostic testing and screening |

| |Reading, article: Understanding Odds Ratios (on Coursework) |

|30 |Statistical Tests for Time-to-Event Data (Survival Analysis): time-to-event data, Kaplan-Meier, Cox regression, hazard ratios |

| |Reading, article: Making Sense of Intention to Treat (on Coursework) |

|June | |

| | |

|6 |FINAL EXAM: in-class, multiple choice exam |

| | |

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