|Authors:||Drew A. Linzer, Jeffrey B. Lewis|
|Title:||poLCA: An R Package for Polytomous Variable Latent Class Analysis|
|Abstract:||poLCA is a software package for the estimation of latent class and latent class regression models for polytomous outcome variables, implemented in the R statistical computing environment. Both models can be called using a single simple command line. The basic latent class model is a finite mixture model in which the component distributions are assumed to be multi-way cross-classification tables with all variables mutually independent. The latent class regression model further enables the researcher to estimate the effects of covariates on predicting latent class membership. poLCA uses expectation-maximization and Newton-Raphson algorithms to find maximum likelihood estimates of the model parameters.|
Page views:: 14128. Submitted: 2007-02-15. Published: 2011-06-14.
poLCA: An R Package for Polytomous Variable Latent Class Analysis
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.