Analysis of Longitudinal Data by Peter Diggle (English) Hardcover Book

Description: Analysis of Longitudinal Data by Peter Diggle, Patrick Heagerty, Kung-Yee Liang, Scott Zeger This text has been revised and expanded and contains an additional two chapters. The first of these discusses fully parametric models for discrete repeated measures data. The second explores statistical models for time-dependent predictors where there may be feedback between the predictor and response variables. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher 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 enablethe reader to reproduce the authors 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. Author Biography 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. Table of Contents 1: Introduction2: Design considerations3: Exploring longitudinal data4: General linear models5: 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 topicsAppendixBibliographyIndex Review `Review from previous edition The book is readable, well-written, and amply illustratedTechnometrics, August 1995`It belongs in the possession of every statistician who encouters longitudinal data.Journal of the American Statistical Association Promotional 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. Long 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 enablethe reader to reproduce the authors 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. Review Text `Review from previous edition The book is readable, well-written, and amply illustratedTechnometrics, August 1995`It belongs in the possession of every statistician who encouters longitudinal data.Journal of the American Statistical Association Review Quote 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. Promotional "Headline" 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 Feature A thorough and expanded version of a classic textImportant reference for professional statisticians as well as for graduate students Details ISBN0198524846 Author Scott Zeger Series Oxford Statistical Science Series Language English Edition 2nd ISBN-10 0198524846 ISBN-13 9780198524847 Media Book Format Hardcover Series Number 25 Year 2002 Replaces 9780198522843 Affiliation University of Lancaster Short Title ANALYSIS OF LONGITUDINAL DATA Imprint Oxford University Press Place of Publication Oxford Country of Publication United Kingdom DOI 10.1604/9780198524847 UK Release Date 2002-06-20 AU Release Date 2002-06-20 NZ Release Date 2002-06-20 Illustrations numerous tables and figures Birth 1927 Death 1955 Position Assistant Professor of Psychiatry Qualifications MD, MPH Pages 398 Publisher Oxford University Press Edition Description 2nd Revised edition Publication Date 2002-06-20 Alternative 9780199676750 DEWEY 519.53502457 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. 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