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Generalized Linear Models with Random Effects

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Generalized Linear Models with Random Effects

Unified Analysis via h-likelihood

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Generalized Linear Models with Random Effects by Youngjo Lee
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Description

Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors. Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible. By maximizing and deriving other quantities from h-likelihood, they also demonstrate how to use a single algorithm for all members of the class, resulting in a faster algorithm as compared to existing alternatives. Complementing theory with examples, many of which can be run by using the code supplied on the accompanying CD, this book is beneficial to statisticians and researchers involved in the above applications as well as quality-improvement experiments and missing-data analysis.
Release date NZ
July 1st, 2006
Country of Publication
United States
Illustrations
54 black & white illustrations, 65 black & white tables
Imprint
Chapman & Hall/CRC
Pages
416
Dimensions
152x229x29
ISBN-13
9781584886310
Product ID
2056446

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