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

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