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. 2007;14(4):671-694.
doi: 10.1080/10705510701575602.

PROC LCA: A SAS Procedure for Latent Class Analysis

Stephanie T Lanza  1 , Linda M Collins, David R Lemmon, Joseph L Schafer
Affiliations

PROC LCA: A SAS Procedure for Latent Class Analysis

Stephanie T Lanza et al. Struct Equ Modeling. 2007.

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.

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Figures

FIGURE 1
FIGURE 1
Class membership probabilities as a function of whether adolescents skipped school in the past 30 days.
FIGURE 2
FIGURE 2
Class membership probabilities as a function of grades in school (standardized).
See this image and copyright information in PMC

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