Generalized linear models with random effects : unified analysis via h-likelihood

✍ Scribed by Lee, Youngjo; Nelder, John A.; Pawitan, Yudi

Publisher: CRC Press
Year: 2017
Tongue: English
Leaves: 467
Series: Monographs on statistics and applied probability (Series) 153
Edition: Second edition
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical basis of the methodology, new developments in variable selection and multiple testing, and new examples and applications. Read more...

Abstract: This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical basis of the methodology, new developments in variable selection and multiple testing, and new examples and applications. It includes an R package for all the methods and examples that supplement the book

✦ Table of Contents

Content: Classical likelihood theory --
Generalized linear models --
Quasi-likelihood --
Extended likelihood inferences --
Normal linear mixed models --
Hierarchical GLMS --
HGLMs with structured dispersion --
Correlated random effects for HGLMs --
Smoothing --
Double HGLMs --
Variable selection and sparsity models --
Multivariate and missing data analysis --
Multiple testing --
Random effect models for survival data.

✦ Subjects

Linear models (Statistics);Generalized estimating equations;MATHEMATICS / Applied;MATHEMATICS / Probability & Statistics / General;Statistical Theory & Methods;Statistical Computing;Mathematics & Statistics for Engineers

📜 SIMILAR VOLUMES

Generalized Linear Models with Random Ef

📁 Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood

✍ Youngjo Lee, John A. Nelder, Yudi Pawitan 📂 Library 📅 2006 🏛 Chapman and Hall/CRC 🌐 English

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 ra

Generalized Linear Models with Random Ef

📁 Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood, Second Edition

✍ Lee, Youngjo;Nelder, John A;Pawitan, Yudi 📂 Library 📅 2017;2018 🏛 CRC Press; Chapman and Hall/CRC 🌐 English

Generalized Linear Models with Random Ef

📁 Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood (Chapman & Hall CRC Monographs on Statistics & Applied Probability)

✍ Youngjo Lee, John A. Nelder, Yudi Pawitan 📂 Library 📅 2006 🏛 Chapman and Hall/CRC 🌐 English

Statistical Modelling of Survival Data w

📁 Statistical Modelling of Survival Data with Random Effects: H-Likelihood Approach

✍ Il Do Ha,Jong-Hyeon Jeong,Youngjo Lee (auth.) 📂 Library 📅 2017 🏛 Springer Singapore 🌐 English

<p>This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the

A Monte Carlo EM algorithm for generaliz

📁 A Monte Carlo EM algorithm for generalized linear mixed models with flexible random effects distribu

✍ Chen J., Zhang D. 📂 Library 🌐 English

Maximum likelihood estimation in random

📁 Maximum likelihood estimation in random effects cure rate models with nonignorable missing covariates

✍ Herring R.H., Ibrahim J.G. 📂 Library 📅 2002 🌐 English