Models for Discrete Longitudinal Data
Springer-Verlag New York Inc.
978-1-4419-2043-0 (ISBN)
Motivating Studies.- Generalized Linear Models.- Linear Mixed Models for Gaussian Longitudinal Data.- Model Families.- The Strength of Marginal Models.- Likelihood-based Marginal Models.- Generalized Estimating Equations.- Pseudo-Likelihood.- Fitting Marginal Models with SAS.- Conditional Models.- Pseudo-Likehood.- From Subject-specific to Random-effects Models.- The Generalized Linear Mixed Model (GLMM).- Fitting Generalized Linear Mixed Models with SAS.- Marginal versus Random-effects Models.- The Analgesic Trial.- Ordinal Data.- The Epilepsy Data.- Non-linear Models.- Pseudo-Likelihood for a Hierarchical Model.- Random-effects Models with Serial Correlation.- Non-Gaussian Random Effects.- Joint Continuous and Discrete Responses.- High-dimensional Joint Models.- Missing Data Concepts.- Simple Methods, Direct Likelihood, and Weighted Generalized Estimating Equations.- Multiple Imputation and the Expectation-Maximization Algorithm.- Selection Models.- Pattern-mixture Models.- Sensitivity Analysis.- Incomplete Data and SAS.
Erscheint lt. Verlag | 1.12.2010 |
---|---|
Reihe/Serie | Springer Series in Statistics |
Zusatzinfo | XXII, 687 p. |
Verlagsort | New York, NY |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik |
Studium ► Querschnittsbereiche ► Epidemiologie / Med. Biometrie | |
ISBN-10 | 1-4419-2043-9 / 1441920439 |
ISBN-13 | 978-1-4419-2043-0 / 9781441920430 |
Zustand | Neuware |
Haben Sie eine Frage zum Produkt? |
aus dem Bereich