Components of Variance (Hardcover)

KEY MODELS AND CONCEPTS
Preliminaries
Some Simple Special Models
A Distributional Specification
Two Key Concepts
Objectives
Bibliographic Notes
Further Results and Exercises
ONE-WAY BALANCED CASE
Analysis of Variance
Some More Assumptions
Synthesis of Variance
Finite Population Aspects
Formulation
Some More Theory
Bibliographic Notes
Computational/Software Notes
Further Results and Exercises
MORE GENERAL BALANCED ARRANGEMENTS
Preliminaries
Components of Covariance and Regression
Time as a Factor
Bayesian Considerations
Measurement Error in Regression
Heterogeneous Variability
Design Issues
Bibliographic Notes
Computational/Software Notes
Further Results and Exercises
UNBALANCED SITUATIONS
Introduction
One-Way Classification
A More General Formulation
A Special Case
Synthesis of Studies
Maximum Likelihood and REML
A Different Approach
Bibliographic Notes
Computational/Software Notes
Further Results and Exercises
NON-NORMAL PROBLEMS
Preliminaries
Poisson Distribution
Binomial Distribution
Survival Data
Some Extensions
A More General Formulation
Generalized Linear Mixed Model
Development of Analysis
An Outline Example
Bibliographic Notes
Computational/Software Notes
Further Results and Exercises
MODEL EXTENSIONS AND CRITICISM
Introduction
Modifications of Structure
Outliers
Robust Estimation of an Internal Variance
Model Assessment: Predicting Exceedances
Analysis of Variability Within Small Groups
Analysis by Model Elaboration: A Nonlinear Form
Analysis by Model Elaboration: Transformation
Nonparametric Estimation of Distributional Form
Bibliographic Notes
Further Results and Exercises
APPENDIX: Fitting Separate Logistic Regressions to the ANZICS Data
REFERENCES
AUTHOR INDEX
SUBJECT INDEX