
Analysis of Longitudinal Data
NCS P
Oxford University Press
2nd Edition
Published on 14. March 2013
Book
Paperback/Softback
400 pages
978-0-19-967675-0 (ISBN)
Description
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 second edition, published for the first time in paperback, 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.
Reviews / Votes
The book is readable, well-written, and amply illustrated * Technometrics, August 1995 (previous edition) * It belongs in the possession of every statistician who encouters longitudinal data. * Journal of the American Statistical Association * . . . provides an excellent bridge between novel concepts in theoretical statistics and their potential use in applied research. * Statistics in Medicine * The topics covered are too numerous to dwell on here ... If your work involves longitudinal data and you wish to update, this book will serve you very well. As a quick look-up, it is very useful. * Pharmaceutical Statistics * The authors conclude each chapter with a helpful summary or conclusion, often indicating further reading. Helpfully, they also mention the topics that they have chosen not to present, together with other recommended books for you to follow up ... They have also chosen a good selection of examples, many of them medical, with which the various methods are clearly illustrated. * Pharmaceutical Statistics * Readers with interests across a wide spectrum of application areas will find the ideas relevant and interesting ... The book is readable and well written ... It belongs to the possession of every statistician who encounters longitudinal data. * Zentralblatt MATH *More details
Series
Edition
2nd Revised edition
Language
English
Place of publication
Oxford
United Kingdom
Target group
Professional and scholarly
Graduate students and researchers in probability and statistics, professionals in biostatistics
Edition type
Revised edition
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 21 mm
Weight
605 gr
ISBN-13
978-0-19-967675-0 (9780199676750)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Peter Diggle | Patrick Heagerty | Kung-Yee Liang
Analysis of Longitudinal Data
E-Book
03/2013
2nd Edition
OUP eBook
€53.99
Available for download

Peter Diggle | Patrick Heagerty | Kung-Yee Liang
Analysis of Longitudinal Data
E-Book
03/2013
2nd Edition
OUP eBook
€53.99
Available for download
Persons
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
Patrick Heagerty, Biostatistics department University of Washington
Kung-Yee Liang, Biostatistics department, Johns Hopkins University
Scott Zeger, Biostatistics department, Johns Hopkins University
Author
Department of Mathematics and Statistics, University of Lancaster
Biostatistics department University of Washington
Biostatistics department, Johns Hopkins University
Biostatistics department, Johns Hopkins University
Content
1. Introduction ; 2. Design considerations ; 3. Exploring longitudinal data ; 4. General linear models ; 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 ; Bibliography ; Index