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Linear Mixed Models for Longitudinal Data

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this;

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Mixed Effects Models for Complex Data

and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating;

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Mixed Effects Models for Complex Data

and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating;

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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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Generalized, Linear, and Mixed Models

data, which now includes a discussion of generalized linear models, modern advances in longitudinal data analysis, and the use between and;

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Models For Discrete Longitudinal Data

The linear mixed model has become the main parametric tool for the analysis of continuous longitudinal data, as the authors discussed;

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

chapters. The chapters are organized in four parts. Volume II discusses generalized linear mixed models for binary, categorical, count, and;

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Generalized Linear and Nonlinear Models for Correlated Data

Edward F. Vonesh's "Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS" is devoted to the;

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Multilevel and Longitudinal Modeling Using Stata, Volume I

extensions of a linear regression model. The mixed-model foundation and the in-depth coverage of the mixed-model principles provided in volume I for;

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Methods and Applications of Longitudinal Data Analysis

Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical;

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Analysis Of Longitudinal Data

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis;

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Generalized Linear Mixed Models

normally distributed data, this one adopts a generalized mixed model approach throughout: data for linear modeling need not be normally distributed;

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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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A First Course in Linear Model Theory

for linear models has been expanded into two chapters. Expanded coverage of multiple comparisons, random and mixed effects models, model;

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Mixed-Effects Models in S and S-PLUS

An overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as;

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Mixed-Effects Models in S and S-PLUS

An overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as;

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Statistical Tests for Mixed Linear Models

treatment for these models at an advanced level. Statistical Tests for Mixed Linear Models:* Combines analysis and testing in one self-contained;

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Linear Model Theory

A precise and accessible presentation of linear model theory, illustrated with data examples Statisticians often use linear models for data;

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Statistical Methods for Drug Safety

selection bias in the analysis of large-scale longitudinal observational data. Choose the Right Statistical Approach for Analyzing Your Drug Safety;

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Statistical Methods for Drug Safety

selection bias in the analysis of large-scale longitudinal observational data. Choose the Right Statistical Approach for Analyzing Your Drug;

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Applied Longitudinal Analysis

Praise for the First Edition ...[this book] should be on the shelf of everyone interested in ...longitudinal data analysis. Journal;

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Analysis Of Longitudinal Data 2nd

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis;

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Multilevel Modeling of Social Problems

, and Gaussian end points using SAS's generalized linear mixed models (GLIMMIX) procedure. * Selects appropriate covariance structures for;

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Multilevel Modeling of Social Problems

, and Gaussian end points using SAS's generalized linear mixed models (GLIMMIX) procedure. * Selects appropriate covariance structures for;

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Linear Mixed Models

comprehensive update of the available tools for fitting linear mixed-effects models in the newest versions of SAS, SPSS, R, Stata, and HLM. All examples;

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Generalized Linear and Nonlinear Models for Correlated Data

Edward F. Vonesh's Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS is devoted to the;

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