Latent Class and Latent Transition Analysis : With Applications in the Social, Behavioral, and Health Sciences

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Format: eBook
Pub. Date: 2010-01-01
Publisher(s): Wiley
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Summary

One of the few books on latent class analysis (LCA) and latent transition analysis (LTA) with a comprehensive treatment of longitudinal latent class models, Latent Class and Latent Transition Analysis reflects improvements in statistical computing as the most up-to-date reference for theoretical, technical, and practical issues in cross-sectional and longitudinal data. Plentiful examples enable the reader to acquire a thorough conceptual and technical understanding and to apply techniques to address empirical research questions. Researchers seeking an advanced introduction to LCA and LTA and graduate students will benefit from this text.

Table of Contents

List of Figures
List of Tables
Acknowledgments
Acronyms
Fundamentals
General Introduction
Overview
Conceptual foundation and brief history of the latent class model
Why select a categorical latent variable approach?
Scope of this book
Empirical example of LCA: Adolescent delinquency
Empirical example of LTA: Adolescent delinquency
About this book
The examples in this book
Software
Additional resources: The book's web site
Suggested supplemental readings
Points to remember
What's next
The latent class model
Overview
Empirical example: Pubertal development
The role of item-response probabilities to label the latent classes in the pubertal development example
Empirical example: Health risk behaviors
LCA: Model and notation
Suggested supplemental readings
Points to remember
What's next
The relation between the latent variable and its indicators
Overview
The latent class measurement model
Homogeneity and latent class separation
The precision with which the observed variables measure the latent variable
Expressing the degree of uncertainty: Mean posterior probabilities and entropy
Points to remember
What's next
Parameter estimation and model selection
Overview
Maximum Likelihood estimation
Model fit and model selection
Finding the ML solution
Empirical example of using many starting values
Empirical examples of selecting the number of latent classes
More about parameter restrictions
Standard errors
Suggested supplemental readings
Points to remember
What's next
Advanced LCA
Multiple-group LCA
Overview
Introduction
Multiple-group LCA: Model and notation
Computing the number of parameters estimated
Expressing group differences in the LCA model
Measurement invariance
Establishing whether the number of latent classes is identical across groups
Establishing invariance of item-response probabilities across groups
Interpretation when measurement invariance does not hold
Strategies when measurement invariance does not hold
Significant differences and important differences
Testing equivalence of latent class prevalences across groups
Suggested supplemental readings
Points to remember
What's next
LCA with Covariates
Overview
Empirical example: Positive health behaviors
Preparing to conduct LCA with covariates
LCA with covariates: Model and notation
Hypothesis testing in LCA with covariates
Interpretation of the intercepts and regression coefficients
Empirical examples of LCA with a single covariate
Empirical example of multiple covariates and interaction terms
Multiple-group LCA with covariates: Model and notation
Grouping variable or covariate?
Use of a Bayesian prior to stabilize estimation
Binomial logistic regression
Suggested supplemental readings
Points to remember
What's next
Latent Class Models for Longitudinal Data
RMLCA and LTA
Overview
RMLCA
LTA
LTA model parameters
LTA: Model and notation
Degrees of freedom associated with latent transition models
Empirical example: Adolescent depression
Empirical example: Dating and sexual risk behavior
Interpreting what a latent transition model reveals about change
Parameter restrictions in LTA
Testing the hypotheses of measurement invariance across times
Testing the hypotheses about change between times
Relation between RMLCA and LTA
Invariance of the transition probability matrix
Suggested supplemental readings
Points to remember
What's next
Multiple-Group LTA and LTA with Covariates
Overview
LTA with a grouping variable
Multiple-group LTA: Model and notation
Computing the number of parameters estimated in multiple-group latent transition models
Hypothesis tests concerning group differences: General consideration
Overall hypothesis tests about group differences in LTA
Testing the hypothesis of equality of latent status prevalences
Testing the hypothesis of equality of transition probabilities
Incorporating covariates in LTA
LTA with covariates: Model and notation
Hypothesis testing in LTA with covariates
Including both a grouping variable and a covariate in LTA
Binomial logistic regression
The relation between multiple-group LTA and LTA with a covariate
Suggested supplemental readings
Points to remember
Topic Index
Author Index
Table of Contents provided by Publisher. All Rights Reserved.

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