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Latent Class and Latent Transition Analysis - With Applications in the Social, Behavioral, and Health Sciences (Hardcover)
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Latent Class and Latent Transition Analysis - With Applications in the Social, Behavioral, and Health Sciences (Hardcover)
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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 SASr environment. A related Web site
houses information on
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