Analysis of Longitudinal Data, Second Edition

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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.

Author(s): Peter Diggle, Patrick Heagerty, Kung-Yee Liang, Scott Zeger
Edition: 2
Year: 2002

Language: English
Pages: 199

Contents
......Page 6
5-12
......Page 7
13-14
......Page 8
1 Introduction
......Page 9
2 Design considerations
......Page 20
3 Exploring long. data
......Page 25
4 GLM for long. data
......Page 36
5 Parametric models for covariance structure
......Page 49
6 Analysis of variance methods
......Page 66
7 GLM for long. data
......Page 73
8 Marginal models
......Page 80
9 Random effects models
......Page 94
10 Transition models
......Page 105
11 Likelihood methods for categorical data
......Page 114
12 Time-dependent covariates
......Page 132
13 Missing values
......Page 151
14 Additional topics
......Page 169
Appendix
......Page 178
Bibliography
......Page 184
Index
......Page 194