BayesLCA: An R Package for Bayesian Latent Class Analysis

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Authors Arthur J. White, Thomas Brendan Murphy
Journal/Conference Name Journal of Statistical Software
Paper Category
Paper Abstract The BayesLCA package for R provides tools for performing latent class analysis within a Bayesian setting. Three methods for fitting the model are provided, incorporating an expectation-maximization algorithm, Gibbs sampling and a variational Bayes approximation. The article briefly outlines the methodology behind each of these techniques and discusses some of the technical difficulties associated with them. Methods to remedy these problems are also described. Visualization methods for each of these techniques are included, as well as criteria to aid model selection.
Date of publication 2014
Code Programming Language R
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