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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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Generalized, Linear, and Mixed Models

style and wealth of illustrative exercises, Generalized, Linear, and Mixed Models , Second Edition is an ideal book for courses on generalized;

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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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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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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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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

The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive;

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Extending The Linear Model With R

count models, linear discriminant analysis, and sandwich and robust estimation for generalized linear models (GLMs) Revised chapters on random;

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SAS for Mixed Models, Second Edition

, multilocation, and repeated measures models hierarchical models with nested random effects analysis of covariance models spatial correlation models;

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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

Thoroughly updated throughout, A First Course in Linear Model Theory, Second Edition is an intermediate-level statistics text that fills an;

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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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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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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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Statistical Models

sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain;

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Statistical Models

sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain;

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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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Confidence Intervals in Generalized Regression Models

A Cohesive Approach to Regression Models Confidence Intervals in Generalized Regression Models introduces a unified representation-the;

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Confidence Intervals in Generalized Regression Models

A Cohesive Approach to Regression Models Confidence Intervals in Generalized Regression Models introduces a unified representation-the;

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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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Economet Anal Cross Sectn & Panel

. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research;

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Linear Models in Statistics

linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition;

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Linear Models

edition. Linear Models, Second Edition is written in such a way as to be self-contained for a person with a background in basic statistics;

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Statistical Modelling of Survival Data with Random Effects

This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h;

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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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