B1218
Title: multilevLCA: An R package for single-level and multilevel latent class analysis with covariates
Authors: Roberto Di Mari - Universita' di Catania, Dipartimento di Economia e Impresa (Italy)
Zsuzsa Bakk - Leiden university (Netherlands)
Jennifer Oser - Ben-Gurion University (Israel)
Jouni Kuha - London School of Economics (United Kingdom)
Johan Lyrvall - University of Catania (Italy) [presenting]
Abstract: The software contribution multilevLCA is an open-source R package based on C++ routines which implements methodological innovations in multilevel latent class modelling with covariates. Maximum likelihood estimates are computed using the classic one-step estimator or by means of the more advantageous two-step estimator. When the number of classes is unknown, semi-automatic model selection can be performed using the sequential approach or simultaneous approach. In addition, the package features output visualization of any of the available model specifications. The multilevLCA toolkit is illustrated by means of an application on citizenship norms data.
