CLCM: Estimate Confirmatory Latent Class Models

Estimate confirmatory latent class models for a variety of item response types that are encountered in the clinical field. One or two timepoints are supported. Latent regression estimation can be performed, allowing for comparisons of longitudinal latent class assignments (e.g., treatment success/failure) across observed groups (e.g., treatment arms in clinical trials). Fit statistics C2 (a limited-information goodness-of-fit statistic), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) are available as well. Methods are described in Iaconangelo (2026) <doi:10.5281/zenodo.22663151>.

Version:	0.1.1
Imports:	Matrix, numDeriv, stats, utils
Suggests:	ggplot2, knitr, nnet, rmarkdown, scales
Published:	2026-09-21
DOI:	10.32614/CRAN.package.CLCM (may not be active yet)
Author:	Charlie Iaconangelo [aut, cre]
Maintainer:	Charlie Iaconangelo <charles.iaconangelo at gmail.com>
BugReports:	https://github.com/CJangelo/CLCM/issues
License:	GPL (≥ 3)
URL:	https://github.com/CJangelo/CLCM, https://cjangelo.github.io/CLCM/
NeedsCompilation:	no
CRAN checks:	CLCM results

Documentation:

Reference manual:	CLCM.html , CLCM.pdf
Vignettes:	Introduction and Basic Examples (source, R code) C2 Fit Statistics (source, R code) CLCM with Greater than 2 Latent Classes (source, R code) Multinomial Latent Regression (source, R code) Longitudinal CLCM & Transition Matrix (source, R code) Longitudinal CLCM with Latent Regression (source, R code) Longitudinal CLCM with Multinomial Latent Regression (source, R code)

Downloads:

Package source:	CLCM_0.1.1.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): CLCM_0.1.1.tgz, r-release (x86_64): CLCM_0.1.1.tgz, r-oldrel (x86_64): CLCM_0.1.1.tgz

Linking:

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