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Analysis of Longitudinal Data 2ND Edition

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Analysis of Longitudinal Data 2ND Edition Cover

 

Synopses & Reviews

Publisher Comments:

This book provides a self-contained account of a wide range ofstatistical methods for the analysis of longitudinal data. Emphasizing the biomedical and agricultural sciences, the book covers each method's applicability and underlying statistical theory. Major topics include: design considerations, exploratory methods of analysis, linear models for continuous data, generalized linear models for discrete data, and models and methods for handling data with missing values. Worked examples are presented throughout and an appendix covers some basic statistical principles. This cogent and clear text will be welcomed by students across a wide range of the sciences.

Book News Annotation:

Aiming their work at the first year postgraduate statistic students, the authors (from Lancaster U., the U. of Washington, and Johns Hopkins U.) describe statistical models and methods for the analysis of longitudinal data, strongly emphasizing applications in biological and health sciences. After covering basic issues of design and exploratory analysis, they develop linear models and associated statistical methods for data sets in which the response variable is a continuous measurement. Later chapters examine generalized linear models for discrete response variables. Also explored are stochastic processes that may interact with response processes, solutions to the problems of missing values in longitudinal studies, and additional topics.
Annotation c. Book News, Inc., Portland, OR (booknews.com)

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.

Synopsis:

Includes bibliographical references (p. [349]-368) and index.

Table of Contents

1. Introduction

2. Design considerations

3. Exploring longitudinal data

4. General linear models for longitudinal data

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 Statistical background

Bibliography

Index

Product Details

ISBN:
9780198524847
Author:
Diggle, Peter
Author:
Heagerty, Patrick
Author:
null, Kung-Yee
Author:
null, Peter
Author:
Null, Scott
Author:
null, Patrick
Author:
Scott Zeger
Author:
Liang, Kung-Yee
Publisher:
Oxford University Press
Location:
Oxford
Subject:
Statistics
Subject:
Epidemiology
Subject:
Time-series analysis
Subject:
Multivariate analysis
Subject:
Probability & Statistics - Multivariate Analysis
Subject:
Mathematics | Probability
Subject:
Mathematics | Probability and Statistics
Subject:
Mathematics | Probability & Statistics
Subject:
Mathematics - General
Copyright:
Edition Number:
2
Edition Description:
Second
Series:
Oxford Statistical Science Series
Series Volume:
13
Publication Date:
20020829
Binding:
Hardback
Grade Level:
College/higher education:
Language:
English
Illustrations:
53 illus.
Pages:
396
Dimensions:
6.4 x 9.3 x 1.1 in 1.594 lb

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Analysis of Longitudinal Data 2ND Edition Used Hardcover
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Product details 396 pages Oxford University Press - English 9780198524847 Reviews:
"Synopsis" by , 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.

"Synopsis" by , Includes bibliographical references (p. [349]-368) and index.
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