Random Effect and Latent Variable Model Selection

From the reviews: "This book is a collection of review papers, of developments in a young and fast-moving field. It consists of two parts; on random effects models, and factor analysis and structural equation models. Within both of these, there is the familiar divide between frequentist and Bayesian methods, which receive separate reviews. The Bayesian methods are typically more recent developments, although almost all of the material covered is from the late 1980s and beyond. ...This book offers researchers in this area several snapshots of current lines of research. Taken individually, the chapters offer concise and clear reviews of the more mature frequentist field, as well as clearly written introductions to newer Bayesian work." (Biometrics, Summer 2009, 65, 993) "The topics are appropriate and timely. The chapters are well written and well organized. ... this book presents methods incorporating model uncertainty in random-effects and latent variable models. This concise, self-contained ... application-based volume will be beneficial to graduate students and researchers interested in both theory and application. It also is suitable as a text for a graduate seminar ... . I must commend the editor for providing a nice summary and discussion on the topics covered in the book ... I enjoyed reading it!" (Technometrics, Vol. 51 (2), May, 2009)

• Random Effects Models.- Likelihood Ratio Testing for Zero Variance Components in Linear Mixed Models.- Variance Component Testing in Generalized Linear Mixed Models for Longitudinal/Clustered Data and other Related Topics.- Bayesian Model Uncertainty in Mixed Effects Models.- Bayesian Variable Selection in Generalized Linear Mixed Models.- Factor Analysis and Structural Equations Models.- A Unified Approach to Two-Level Structural Equation Models and Linear Mixed Effects Models.- Bayesian Model Comparison of Structural Equation Models.- Bayesian Model Selection in Factor Analytic Models.