Multivariable Methods
Contents
Page 1
Introduction
Learning Objectives
Page 2
Confounding
Determining Whether a Variable is a Confounder
Page 3
A Stratified Analysis
The Cochran-Mantel-Haenszel Method
Data Layout for Cochran-Mantel-Haenszel Estimates
Page 4
Effect Modification
Page 5
Introduction to Correlation and Regression Analysis
Correlation Analysis
Example - Correlation of Gestational Age and Birth Weight
Page 6
Regression Analysis
Simple Linear Regression
BMI and Total Cholesterol
BMI and HDL Cholesterol
Comparing Mean HDL Levels With Regression Analysis
The Controversy Over Environmental Tobacco Smoke Exposure
Page 7
Multiple Linear Regression Analysis
Controlling for Confounding With Multiple Linear Regression
Relative Importance of the Independent Variables
Evaluating Effect Modification With Multiple Linear Regression
"Dummy" Variables in Regression Models
Example of the Use of Dummy Variables
Page 8
Multiple Logistic Regression Analysis
Example of Logistic Regression - Association Between Obesity and CVD
Example - Risk Factors Associated With Low Infant Birth Weight
Page 9
Summary
Page 10
References
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