BayesLCA: An R Package for Bayesian Latent Class Analysis

Arthur White and Thomas Brendan Murphy

Journal of Statistical Software, 2014, vol. 061, issue i13

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: 2014-11-25
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:061:i13

DOI: 10.18637/jss.v061.i13

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