Models for Discrete Longitudinal Data

Name: Models for Discrete Longitudinal Data
Brand: Springer-Verlag New York Inc.
SKU: 9780387251448
Price: 76434 HUF
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Szerző: Geert Molenberghs, Geert Verbeke

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer-Verlag New York Inc.

Elérhetőség: Beszállítói készleten

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This book provides a comprehensive treatment on modeling approaches for non-Gaussian repeated measur...

Információk a könyvről

Szerző

Geert Molenberghs, Geert Verbeke

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

2006

oldal

687

EAN

9780387251448

ISBN

0387251448

Enbook ID

01381250

Kiadó

Springer-Verlag New York Inc.

Súly

1122

Méretek

164 x 241 x 41

Teljes leírás

This book provides a comprehensive treatment on modeling approaches for non-Gaussian repeated measures, possibly subject to incompleteness. The authors begin with models for the full marginal distribution of the outcome vector. This allows model fitting to be based on maximum likelihood principles, immediately implying inferential tools for all parameters in the models. At the same time, they formulate computationally less complex alternatives, including generalized estimating equations and pseudo-likelihood methods. They then briefly introduce conditional models and move on to the random-effects family, encompassing the beta-binomial model, the probit model and, in particular the generalized linear mixed model. Several frequently used procedures for model fitting are discussed and differences between marginal models and random-effects models are given attention.§The authors consider a variety of extensions, such as models for multivariate longitudinal measurements, random-effects models with serial correlation, and mixed models with non-Gaussian random effects. They sketch the general principles for how to deal with the commonly encountered issue of incomplete longitudinal data. The authors critique frequently used methods and propose flexible and broadly valid methods instead, and conclude with key concepts of sensitivity analysis.§Without putting too much emphasis on software, the book shows how the different approaches can be implemented within the SAS software package. The text is organized so the reader can skip the software-oriented chapters and sections without breaking the logical flow.

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Models for Discrete Longitudinal Data

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