Analysis of Longitudinal Data / Edition 2

by Peter Diggle, Patrick Heagerty, Kung-Yee Liang, Scott Zeger

Overview

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.

Product Details

ISBN-13:	9780198524847
Publisher:	Oxford University Press
Publication date:	08/29/2002
Series:	Oxford Statistical Science Series , #25
Edition description:	REV
Pages:	398
Product dimensions:	9.30(w) x 6.40(h) x 1.05(d)

About the Author

Peter Diggle, Department of Mathematics and Statistics, University of Lancaster



Patrick Heagerty, Biostatistics department University of Washington


Kung-Yee Liang, Biostatistics department, Johns Hopkins University


Scott Zeger, Biostatistics department, Johns Hopkins University

Table of Contents

1. Introduction2. Design considerations3. Exploring longitudinal data4. General linear models for longitudinal data5. Parametric models for covariance structure6. Analysis of variance methods7. Generalized linear models for longitudinal data8. Marginal models9. Random effects models10. Transition models11. Likelihood-based methods for categorical data12. Time-dependent covariates13. Missing values in longitudinal data14. Additional topicsAppendix Statistical backgroundBibliographyIndex

Editorial Reviews

"...it is well written, with wide coverage of biological and medical applications. It should continue to have a prominent place in libraries, and researchers who are interested in longitudinal data analysis will want a personal copy." —Journal of the American Statistical Association

From the Publisher