Linda M. Collins & Stephanie T. Lanza 
Latent Class and Latent Transition Analysis [EPUB ebook] 
With Applications in the Social, Behavioral, and Health Sciences

A modern, comprehensive treatment of latent class and latent
transition analysis for categorical data
On a daily basis, researchers in the social, behavioral, and
health sciences collect information and fit statistical models to
the gathered empirical data with the goal of making significant
advances in these fields. In many cases, it can be useful to
identify latent, or unobserved, subgroups in a population, where
individuals’ subgroup membership is inferred from their responses
on a set of observed variables. Latent Class and Latent
Transition Analysis provides a comprehensive and unified
introduction to this topic through one-of-a-kind, step-by-step
presentations and coverage of theoretical, technical, and practical
issues in categorical latent variable modeling for both
cross-sectional and longitudinal data.
The book begins with an introduction to latent class and latent
transition analysis for categorical data. Subsequent chapters delve
into more in-depth material, featuring:
* A complete treatment of longitudinal latent class models
* Focused coverage of the conceptual underpinnings of
interpretation and evaluationof a latent class solution
* Use of parameter restrictions and detection of identification
problems
* Advanced topics such as multi-group analysis and the modeling
and interpretation of interactions between covariates
The authors present the topic in a style that is accessible yet
rigorous. Each method is presented with both a theoretical
background and the practical information that is useful for any
data analyst. Empirical examples showcase the real-world
applications of the discussed concepts and models, and each chapter
concludes with a ‘Points to Remember’ section that contains a brief
summary of key ideas. All of the analyses in the book are performed
using Proc LCA and Proc LTA, the authors’ own software packages
that can be run within the SAS® environment. A related Web
site houses information on these freely available programs and the
book’s data sets, encouraging readers to reproduce the analyses and
also try their own variations.
Latent Class and Latent Transition Analysis is an
excellent book for courses on categorical data analysis and latent
variable models at the upper-undergraduate and graduate levels. It
is also a valuable resource for researchers and practitioners in
the social, behavioral, and health sciences who conduct latent
class and latent transition analysis in their everyday work.

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