Analysis of Longitudinal Data

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

ISBN 10: 0198524846 / ISBN 13: 9780198524847

Published by Oxford University Press, GB, 2002

About this Item

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural and biomedical sciences. The main topics discussed are design issues, exploratory methods of analysis, linear models for continuous data, general linear models for discrete data, and models and methods for handling data and missing values. Under each heading, worked examples are presented in parallel with the methodological development, and sufficient detail is given to enable the reader to reproduce the author's results using the data-sets as an appendix. This new edition of Analysis for Longitudinal Data provides a thorough and expanded revision of this important text. It includes two new chapters; the first discusses fully parametric models for discrete repeated measures data, and the second explores statistical models for time-dependent predictors.

Seller Inventory # LU-9780198524847

Bibliographic Details

• Title: Analysis of Longitudinal Data
• Publisher: Oxford University Press, GB
• Publication Date: 2002
• Language: English
• ISBN 10: 0198524846
• ISBN 13: 9780198524847
• Binding: Hardback
• Edition: 2nd Edition
• Condition: New
• Weight: 733 grams

About this title

Synopsis

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.

About the Author

Peter Diggle is in the Department of Mathematics and Statistics, University of Lancaster. Patrick Heagerty is in the Biostatistics Department, University of Washington. Kung-Yee Liang and Scott Zeger are both in the Biostatistics Department, Johns Hopkins University.