poLCA: An R Package for Polytomous Variable Latent Class Analysis

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Authors Drew A. Linzer, Jeffrey Lewis
Journal/Conference Name Journal of Statistical Software
Paper Category
Paper 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.
Date of publication 2011
Code Programming Language R
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