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

Analysis of Longitudinal Data second edition

• Gebundenes Buch

Produktbeschreibung

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.

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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 area of biostatistics (medical statistics). This new edition 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.

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Produktdetails

• Verlag: Oxford University Press
• 2nd edition
• Seitenzahl: 398
• Erscheinungstermin: 29. August 2002
• Englisch
• Abmessung: 243mm x 164mm x 26mm
• Gewicht: 728g
• ISBN-13: 9780198524847
• ISBN-10: 0198524846
• Artikelnr.: 21003555

Inhaltsangabe

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