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Generalized Linear Mixed Models

with linear models that accommodate random model effects and non-Gaussian data. Unlike traditional linear model textbooks that focus on;

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Data Analysis Using Hierarchical Generalized Linear Models with R

advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs;

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Data Analysis Using Hierarchical Generalized Linear Models with R

advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs;

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Generalized, Linear, and Mixed Models

An accessible and self-contained introduction to statistical models-now in a modernized new edition Generalized, Linear, and Mixed Models;

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Generalized Linear Models with Random Effects

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and;

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Multivariate Generalized Linear Mixed Models Using R

members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After;

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

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and;

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Generalized Linear Models with Random Effects

. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood;

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Multilevel and Longitudinal Modeling Using Stata, Volumes I and II, Third Edition

This book examines Stata's treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are;

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Foundations of Linear and Generalized Linear Models

of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to;

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Interaction Effects in Linear and Generalized Linear Models: Examples and Applications Using Stata

Offering a clear set of workable examples with data and explanations, Interaction Effects in Linear and Generalized Linear Models is a;

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A First Course in Linear Model Theory

. Revised or expanded topics include linear fixed, random and mixed effects models, generalized linear models, Bayesian and hierarchical linear;

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Introduction to General and Generalized Linear Models

Bridging the gap between theory and practice for modern statistical model building, Introduction to General and Generalized Linear Models;

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Linear Model Methodology

, heteroscedastic linear models, response surface models with random effects, and linear multiresponse models. The final chapter introduces generalized;

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Extending The Linear Model With R

expanded both in popularity and in the number of packages available. Extending the Linear Model with R: Generalized Linear, Mixed Effects and;

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SAS for Mixed Models, Second Edition

generalized linear mixed models nonlinear mixed models Professionals and students with a background in two-way ANOVA and regression and a basic;

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Linear Model Theory

This book contains 296 exercises and solutions covering a wide variety of topics in linear model theory, including generalized inverses;

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Linear Model Theory

This book contains 296 exercises and solutions covering a wide variety of topics in linear model theory, including generalized inverses;

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Pharmacokinetic-Pharmacodynamic Modeling and Simulation

considerably expands with the addition of three new chapters relating to Bayesian models, Generalized linear and nonlinear mixed effects models, and;

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Asymptotic Analysis of Mixed Effects Models

Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized;

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Asymptotic Analysis of Mixed Effects Models

Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized;

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Richly Parameterized Linear Models

systematic, theory-based understanding of models with random effects. Richly Parameterized Linear Models: Additive, Time Series, and Spatial;

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Richly Parameterized Linear Models

systematic, theory-based understanding of models with random effects. Richly Parameterized Linear Models: Additive, Time Series, and Spatial;

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Generalized Linear and Nonlinear Models for Correlated Data

analysis of correlated response data using SAS, with special emphasis on applications that require the use of generalized linear models or;

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Linear and Generalized Linear Mixed Models and Their Applications

This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. It presents an up-to;

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Linear and Generalized Linear Mixed Models and Their Applications

This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. It presents an up-to;

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Statistical Tests for Mixed Linear Models

An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw;

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