Related Experiment Video
Updated: Jun 18, 2026

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
Published on: September 27, 2019
PROC LCA: A SAS Procedure for Latent Class Analysis
Stephanie T Lanza1, Linda M Collins, David R Lemmon
1The Methodology Center, The Pennsylvania State University.
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.
Related Concept Videos
Statistical Analysis System (SAS)
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Calibration Curves: Linear Least Squares
For data that follow a straight line, the standard method for fitting is the linear...
Comparing the Survival Analysis of Two or More Groups