The new edition of this important text has been completely revised and expanded to become the most up-to-date
and thorough professional reference text in this fast-moving and important area of biostatistics. Two new chapters
have been added on fully parametric models for discrete repeated measures data and on statistical models for time-dependent
predictors where there may be feedback between the predictor and response variables. It also contains the many
useful features of the previous edition such as, design issues, exploratory methods of analysis, linear models
for continuous data, and models and methods for handling data and missing values.
Table of Contents
1. Introduction
2. Design considerations
3. Exploring longitudinal data
4. General linear models for longitudinal data
5. Parametric models for covariance structure
6. Analysis of variance methods
7. Generalized linear models for longitudinal data
8. Marginal models
9. Random effects models
10. Transition models
11. Likelihood-based methods for categorical data
12. Time-dependent covariates
13. Missing values in longitudinal data
14. Additional topics
Appendix Statistical background
Bibliography
Index
