ANALYSIS LONGITUD DATA 2E OSSS

Zusammenfassung 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. Klappentext 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. Inhaltsverzeichnis 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

Auteur
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

Contenu

• 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