Chapter 14. Generalized Linear Mixed Models

14.1

Introduction

526

14.2

Two Examples to Illustrate When Generalized Linear Mixed Models Are Needed

527

 

14.2.1

Binomial Data in a Multi-center Clinical Trial

527

 

14.2.2

Count Data in a Split-Plot Design

528

14.3

Generalized Linear Model Background

529

 

14.3.1

Fixed Effects Generalized Linear Models

529

 

14.3.2

Probability Distributions

531

 

14.3.3

Link Functions and Variance Structure

534

 

14.3.4

Predicting Means from the Inverse Link Function

535

 

14.3.5

Deviance

536

 

14.3.6

Inference Using Estimable Functions

537

14.4

From GLMs to GLMMs

538

 

14.4.1

Incorporating Random Effects

538

 

14.4.2

The Pseudo-likelihood Approach

538

 

14.4.3

The Role of the Scale Parameter

540

 

14.4.4

Estimation Methods in PROC GLIMMIX

541

14.5

Example: Binomial Data in ...

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