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Oxford Statistical Science Ser.: Analysis of Longitudinal Data by Kung-Yee Liang, Peter Diggle, Patrick Heagerty and Scott Zeger (2002, Hardcover)
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- Buy It NowAnalysis of Longitudinal Data, Hardcover by Diggle, Peter J. (EDT); Heagerty,...
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About this product
Product Identifiers
PublisherOxford University Press, Incorporated
ISBN-100198524846
ISBN-139780198524847
eBay Product ID (ePID)1922750
Product Key Features
Number of Pages398 Pages
Publication NameAnalysis of Longitudinal Data
LanguageEnglish
Publication Year2002
SubjectProbability & Statistics / General, Research, Epidemiology
FeaturesRevised
TypeTextbook
AuthorKung-Yee Liang, Peter Diggle, Patrick Heagerty, Scott Zeger
Subject AreaMathematics, Social Science, Medical
SeriesOxford Statistical Science Ser.
FormatHardcover
Dimensions
Item Height1 in
Item Weight24.2 Oz
Item Length9.2 in
Item Width6.1 in
Additional Product Features
Edition Number2
Intended AudienceCollege Audience
LCCN2002-030767
Dewey Edition23
Reviews'Review from previous edition The book is readable, well-written, and amply illustrated'Technometrics, August 1995'It belongs in the possession of every statistician who encouters longitudinal data.'Journal of the American Statistical Association, 'It belongs in the possession of every statistician who encouterslongitudinal data.'Journal of the American Statistical Association, 'Review from previous edition The book is readable, well-written, and amply illustrated'Technometrics, August 1995, 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., . . . provides an excellent bridge between novel concepts in theoretical statistics and their potential use in applied research., 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., "...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, 'It belongs in the possession of every statistician who encouters longitudinal data.'Journal of the American Statistical Association, 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.
Series Volume NumberVol. 25
IllustratedYes
Dewey Decimal519.5/35
Table Of Content1. 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
Edition DescriptionRevised edition
SynopsisThe 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., 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.
LC Classification NumberQA278.D545 2002
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