| Literature DB >> 19953201 |
Stephanie T Lanza1, Linda M Collins, David R Lemmon, Joseph L Schafer.
Abstract
Latent class analysis (LCA) is a statistical method used to identify a set of discrete, mutually exclusive latent classes of individuals based on their responses to a set of observed categorical variables. In multiple-group LCA, both the measurement part and structural part of the model can vary across groups, and measurement invariance across groups can be empirically tested. LCA with covariates extends the model to include predictors of class membership. In this article, we introduce PROC LCA, a new SAS procedure for conducting LCA, multiple-group LCA, and LCA with covariates. The procedure is demonstrated using data on alcohol use behavior in a national sample of high school seniors.Entities:
Year: 2007 PMID: 19953201 PMCID: PMC2785099 DOI: 10.1080/10705510701575602
Source DB: PubMed Journal: Struct Equ Modeling ISSN: 1070-5511 Impact factor: 6.125