Acknowledgments.

PART I: INTRODUCTION TO LONGITUDINAL AND CLUSTERED DATA.

1. Longitudinal and Clustered Data.

2. Longitudinal Data: Basic Concepts.

PART II: LINEAR MODELS FOR LONGITUDINAL CONTINUOUS DATA.

3. Overview of Linear Models for Longitudinal Data.

4. Estimation and Statistical Inference.

5. Modelling the Mean: Analyzing Response Profiles.

6. Modelling the Mean: Parametric Curves.

7. Modelling the Covariance.

8. Linear Mixed Effects Models.

9. Residual Analyses and Diagnostics.

PART III: GENERALIZED LINEAR MODELS FOR LONGITUDINAL DATA.

10. Review of Generalized Linear Models.

11. Marginal Models: Generalized Estimating Equations (GEE).

12. Generalized Linear Mixed Effects Models.

13. Contrasting Marginal and Mixed Effects Models.

PART IV: ADVANCED TOPICS FOR LONGITUDINAL AND CLUSTERED DATA.

14. Missing Data and Dropout.

15. Some Aspects of the Design of Longitudinal Studies.

16. Repeated Measures and Related Designs.

17. Multilevel Models.

Appendix A: Gentle Introduction to Vectors and Matrices.

Appendix B: Properties of Expectations and Variances.

Appendix C: Critical Points for a 50:50 Mixture of Chi-Squared Distributions.

References.

Index.