ABSTRACT

Many methods for analyzing clustered data exist, all with advantages and limitations in particular applications. Compiled from the contributions of leading specialists in the field, Topics in Modelling of Clustered Data describes the tools and techniques for modelling the clustered data often encountered in medical, biological, environmental, and s

chapter 1|12 pages

Introduction

chapter 2|24 pages

Motivating Examples

chapter 3|10 pages

Issues in Modeling Clustered Data

chapter 4|30 pages

Model Families

chapter 5|12 pages

Generalized Estimating Equations

chapter 6|26 pages

Pseudo-likelihood Estimation

chapter 7|12 pages

Pseudo-likelihood Inference

chapter 8|12 pages

Flexible Polynomial Models

chapter 9|18 pages

Assessing the Fit of a Model

chapter 10|16 pages

Quantitative Risk Assessment

chapter 11|22 pages

Model Misspecification

chapter 12|12 pages

Exact Dose-Response Inference

chapter 13|26 pages

Individual Level Covariates

chapter 14|30 pages

Combined Continuous and Discrete Outcomes

chapter 15|10 pages

Multilevel Modeling of Complex Survey Data