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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

presents likelihood-based techniques for statistical modelling using various types of data. Implementations using R are provided throughout the;

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Advanced R Statistical Programming and Data Models

data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R;

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Multivariate Generalized Linear Mixed Models Using R

Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data;

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An Introduction to Generalized Additive Models with R

Generalized Additive Models: An Introduction with R imparts a thorough understanding of the theory and practical applications of GAMs and;

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Generalized Linear Mixed Models

Generalized Linear Mixed Models: Modern Concepts, Methods and Applications presents an introduction to linear modeling using the;

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An Introduction to Generalized Linear Models

on Bayesian analysis. Like its predecessor, this edition presents the theoretical background of generalized linear models (GLMs) before;

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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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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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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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Analysis of Variance, Design, and Regression

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling;

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Analysis of Variance, Design, and Regression

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling;

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Regression Analysis and Linear Models

, generalized linear model, etc. This book presents the complex subject of regression analysis and linear models, in the most comprehensible and easy to;

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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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A Handbook of Statistical Analyses Using R

, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the;

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Generalized Linear Models and Correlated Data Methods

Offers a unified discussion of generalized linear models and correlated data methods Provides information suitable for graduate non;

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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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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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Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data;

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An Introduction to Generalized Linear Models

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on;

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An Introduction to Generalized Linear Models

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on;

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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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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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Generalized Linear Models

adapt their data for this type of analysis, with examples to illustrate the application of GLM.;

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Linear and Generalized Linear Mixed Models and Their Applications

who are interested in using mixed models for statistical data analysis.;

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Linear and Generalized Linear Mixed Models and Their Applications

who are interested in using mixed models for statistical data analysis.;

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