Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models

Comment from the Stata technical group

This text unifies the principles behind latent variable modeling, which includes multilevel, longitudinal, and structural equation models, as well as generalized mixed models, random coefficient models, item response models, factor models, panel models, repeated-measures models, latent-class models, and frailty models. Since latent-variable models are used by researchers from various disciplines with little or no cross-referencing from other disciplines, unifying these models allows readers to separate what the authors refer to as local jargon from the fundamental elements of these models. As such, this text allows readers to gain quick and easy access to models and estimation schemes that have long existed in other disciplines but perhaps are not widely used in their own.

The book consists of two main parts: methodology and applications. Chapters 1–4 provide background information and generalized development of latent variable models. Chapters 5–8 are concerned with techniques of estimation, prediction, and inference. Chapters 9–14 comprise the applications portion of the text, and here the unification from chapters 1–4 is applied to case studies from various fields, including biostatistics, political science, social science, and econometrics.

The models demonstrated in the applications section are fitted using the Stata program gllamm, written by the authors of this text and available from www.gllamm.org.

Table of contents

View table of contents >>