 Presented by Joseph Schafer
Department of Statistics and The Methodology Center
The Pennsylvania State University
Course Outline
Motivation and theory
- Motivating examples
- Ad hoc techniques
- The distribution of missingness
- Implications of MCAR, MAR
Review of longitudinal modeling
- Classical ANOVA
- Linear mixed models
- Nonlinear mixed models
- Semiparametric models using GEE
Computing Session I: Examples of longitudinal modeling in SAS
Multiple imputation for longitudinal settings
- What is MI?
- How MI works
- Frequently asked questions
- Software
- NORM
- Comparing MI and ML
- Auxiliary variables
- PAN
Computing Session II: Comparing MI with NORM to likelihood and marginal modeling
Methods for nonignorable dropout
- Motivation
- Random-coefficient pattern-mixture models
- Extrapolation methods
- Examples and simulations
Computing Session III: Implementing a random-coefficient pattern-mixture model
Weighted Estimating Equations
- The principle of weighting
- WEE
- Doubly robust?
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