multilevLCA: An R Package for Single-Level and Multilevel Latent Class Analysis with Covariates

arXiv (Cornell University)

Abstract

This contribution presents a guide to the R package multilevLCA, which offers a complete and innovative set of technical tools for the latent class analysis of single-level and multilevel categorical data. We describe the available model specifications, mainly falling within the fixed-effect or random-effect approaches. Maximum likelihood estimation of the model parameters, enhanced by a refined initialization strategy, is implemented either simultaneously, i.e., in one-step, or by means of the more advantageous two-step estimator. The package features i) semi-automatic model selection when a priori information on the number of classes is lacking, ii) predictors of class membership, and iii) output visualization tools for any of the available model specifications. All functionalities are illustrated by means of a real application on citizenship norms data, which are available in the package.

Authors 5

1. Johan Lyrvall

   University of Catania

   Affiliation as printed

   University of Catania , Department of Business and Economics ,

2. Roberto Di Mari

   University of Catania

   Affiliation as printed

   University of Catania , Department of Business and Economics ,

3. Zsuzsa Bakk Aachen Department of Methodology and Statistics

   Leiden University

   Affiliation as printed

   Leiden University , Department of Methodology and Statistics ,

4. Jennifer Lynn Oser
   Affiliation as printed

   Ben-Gurion University , Department of Politics and Government ,

5. Jouni Kuha

   London School of Economics and Political Science

   Affiliation as printed

   London School of Economics , Department of Statistics ,