multilevLCA-package {multilevLCA}

Estimates and Plots Single-Level and Multilevel Latent Class Models

Description

Efficiently estimates single- and multilevel latent class models with covariates, allowing for output visualization in all specifications. For more technical details, see Lyrvall et al (2023) <doi:10.48550/arXiv.2305.07276>.

Details

For estimating latent class models, see multiLCA.

For plotting latent class models, see plot.multiLCA

Author(s)

Roberto Di Mari and Johan Lyrvall.

Maintainer: Roberto Di Mari <[e-mail]>

References

Bakk, Z., & Kuha, J. (2018). Two-step estimation of models between latent classes and external variables. Psychometrika, 83, 871-892.

Bakk, Z., Di Mari, R., Oser, J., & Kuha, J. (2022). Two-stage multilevel latent class analysis with covariates in the presence of direct effects. Structural Equation Modeling: A Multidisciplinary Journal, 29(2), 267-277.

Di Mari, Bakk, Z., R., Oser, J., & Kuha, J. (2023). A two-step estimator for multilevel latent class analysis with covariates. Psychometrika.

Lukociene, O., Varriale, R., & Vermunt, J. K. (2010). The simultaneous decision(s) about the number of lower-and higher-level classes in multilevel latent class analysis. Sociological Methodology, 40(1), 247-283.

Examples

data = dataIEA
Y = colnames(dataIEA)[4+1:12]

out = multiLCA(data = data, Y = Y, iT = 2)
out
plot(out, horiz = FALSE)