Division of Biostatistics, School of Public Health, University of Minnsota
1. Introduction (9/7, 9/9)
2. Exploratory Data Analysis (9/9, 9/12)
3. General Linear Models (9/14, 9/16, 9/19)
4. General Linear Models: Case Studies (9/21, 9/23)
5. Linear Mixed Models (9/26, 9/28, 9/30)
6. Linear Mixed Models: Case Studies (10/3, 10/5, 10/7)
7. Review of Generalized Linear Models, Quasi-likelihood, and Generalized Estimating Functions (10/10, 10/12, 10/14)
8. Marginal Model for Categorical Data (10/19, 10/21)
9. Marginal Model for Categorical Data: Case Studies (10/24, 10/26, 10/28)
10. Likelihood-Based Methods for Repeated Binary Data (10/31)
11. Modeling Approaches: Marginal, Random Effects and Transition Models (11/2, 11/4)
12. Generalized Linear Mixed Models (11/7, 11/9, 11/11, 11/14, 11/16)
13. Transition Models (11/18)
14. Time-Dependent Covariates (11/21, 11/23, 11/28)
15. Missing Data in Longitudinal Studies (11/30, 12/2, 12/5)
16. Sample Size Considerations (12/7, 12/9)
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CD4 Count Data |
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Treatment of Lead-Exposed Children Trial (TLC) |
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Orthodontic Data |
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Indonesian Children Health Study (ICHS) |
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Teratology Data |
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Epileptic Seizure Data |
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nlme, geepack, gee, lme4, Design,
lgtdl,
longitudinal. alr
(Alternating Logistic Regression) and yags (Yet
Another GEE Solver), repeated
(non-normal repeated measurements models), gnlm (generalized non-linear
models).