Table of Contents
Overview of Methods for Longitudinal Data Analysis in Alzheimer’s Disease Research
Outline
Introduction- Types of Longitudinal Studies
Importance of Longitudinal Data Analysis
Old Stuff-Single Variable and ANOVA Methods
Advantages
Continuous Data-Mixed Models (SAS Proc Mixed)
Examples of studies using Mixed Models
Disadvantages of Mixed Models
Some Generalizations-Nonlinear Models
Often the models are still not flexible enough, require more subjects and more time points. Numerically messy.
Models for Discrete Data
GLMM vs. GEE
Relative Advantages GLMM vs. GEE
Examples
Other Approachs
Problems in Longitudinal Studies
Some Useful References and Sofware
References
PPT Slide
PPT Slide
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