Analysis of Longitudinal Data - Peter Diggle, Patrick Heagerty, Kung-Yee Liang, Scott Zeger

Analysis of Longitudinal Data

Buch | Softcover
400 Seiten
2013 | 2nd Revised edition
Oxford University Press (Verlag)
978-0-19-967675-0 (ISBN)
69,80 inkl. MwSt
This second edition 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. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.
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.

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

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

Erscheint lt. Verlag 14.3.2013
Reihe/Serie Oxford Statistical Science Series ; 25
Verlagsort Oxford
Sprache englisch
Maße 157 x 233 mm
Gewicht 588 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Mathematik / Informatik Mathematik
Studium Querschnittsbereiche Epidemiologie / Med. Biometrie
Sozialwissenschaften Soziologie
ISBN-10 0-19-967675-5 / 0199676755
ISBN-13 978-0-19-967675-0 / 9780199676750
Zustand Neuware
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