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

05/12/2023
by   Johan Lyrvall, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/10/2023

A two-step estimator for multilevel latent class analysis with covariates

We propose a two-step estimator for multilevel latent class analysis (LC...
research
02/23/2022

baker: An R package for Nested Partially-Latent Class Models

This paper describes and illustrates the functionality of the baker R pa...
research
07/20/2023

Multilevel latent class analysis with covariates: Analysis of cross-national citizenship norms with a two-stage approach

This paper focuses on the substantive application of multilevel LCA to t...
research
02/07/2023

Examination of Nonlinear Longitudinal Processes with Latent Variables, Latent Processes and Latent Classes: The R package NonLinearCurve

We introduce R package NonLinearCurve that provides a series of function...
research
04/07/2023

StepMix: A Python Package for Pseudo-Likelihood Estimation of Generalized Mixture Models with External Variables

StepMix is an open-source software package for the pseudo-likelihood est...
research
09/20/2023

ddtlcm: An R package for overcoming weak separation in Bayesian latent class analysis via tree-regularization

Traditional applications of latent class models (LCMs) often focus on sc...
research
06/03/2018

Data-Free/Data-Sparse Softmax Parameter Estimation with Structured Class Geometries

This note considers softmax parameter estimation when little/no labeled ...

Please sign up or login with your details

Forgot password? Click here to reset