Random Coefficient Models [Hardcover]

Clustering is a phenomenon commonly observed across social science research--students are clustered in classrooms, individuals in households, and companies within industrial sectors, to name but a few examples. This book presents an elementary and systematic introduction to modeling of between-cluster variation, how results are best interpreted, and computational methods for estimation. The book addresses many important issues in the social sciences that can be best described in terms of variation sources and patterns, such as temporal, between-person, and geographical variation. By providing a balanced presentation of the advantages and limitations of these methods, the author has provided an introduction to the subject that will be of great utility to statisticians and students concentrating on social science data analysis.

1. Introduction
2. Analysis of covariance with random effects
3. Examples. Random-effects models
4. Random regression coefficients
5. Examples using random coefficient models
6. Multiple levels of nesting
7. Factor analysis and structural equations
8. GLM with random coefficients
9. Appendix. Asymptotic theory

A major strength is the interweaving of rather involvedmethodology with the analysis of interesting real-life applications. . .provides an interesting and concise introduction to much of the literature on random-effects modeling. --Journal of the American Statistical Association