WELCOME TO
REGRESSION ANALYSIS IN PUBLIC HEALTH RESEARCH
JUNE 21-July 2, 2003
Course Objectives:
1) To improve students' ability to conduct regression analyses to study the relationship of a response variable on multiple predictor variables.
2) To sharpen the students skills in choosing a regression model, and interpreting regression coefficients.
3) The students should feel "comfortable" applying the sharpened skills to continuous responses (linear regression), binary responses (logistic regression) and time-to-event responses (survival analysis).
Course Materials:
Materials will be distributed in class, pdf files of the course materials are provided below:
Topic 1: Multiple Linear Regression
Supplemental Handouts: Standard output from linear regression model fit
Solution to the "You Do" on page 28
Some more work with linear splines
Solution to "Some more work with linear splines"
Testing of multiple regression coefficients
More complicated modeling example
Solution to "More complicated modeling example"
Sample Size and Power Considerations
Data for sample size and power considerations
Data from Topic 1 notes: hospital data
Do Files for Topic 1 notes: topic1v7.do
Topic 2: Logistic Regression
Supplemental Handouts: Lab exercise 4
Rick Thompson's crossval.ado file for performing cross-validation
Do Files for Topic 2 notes: topic2v7.do
Data from Topic 2 notes: kyphosis data
Topic 3: Survival Analysis
Supplemental Handouts: Lab exercise 5
Do Files for Topic 3 notes: topic3v7.do
PROJECT: The project for both the Regression Analyses class and the Regression Analyses Lab are posted below. In addition, the data file (project.dta) and the do-file (project.do) used to create all the figures for the Regression Analyses project file are posted below.
Project for Regression Analyses Course
Solution for Project for Regression Analyses Course
The data set: project.dta
The do-file: project.do
Nice Reference Books for Regression Analyses:
Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis, Harrell, FE Jr. (2001). Springer-Verlag.
Applied Linear Regression, Weisberg, S. (1985). 2nd Ed. Wiley & Sons
Applied Logistic Regression, Hosmer and Lemeshow, 2nd Ed. Wiley
Survival Analysis, Klein and Moeschberger, Springer-Verlag
Statistical Methods in Medical Research, Second Edition. Armitage, P. and Berry, G. 1987. Blackwell Scientific, Oxford. Chapters 10, 12 and 14.
Biostatistics: A Methodology for the Health Sciences. Fisher, L. D. and vanBelle, G. 1993. Wiley, New York, Chapters 11, 13, and 16.
Applied Regression Analysis and other Multivariable Methods. Kleinbaum, D. G. and Kupper, L. L. 1978. Duxbury Press, Boston. Chapters 10, 12, 15 and 16.