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cff-version: 1.2.0
message: 'To cite package "CLCM" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'CLCM: Estimate Confirmatory Latent Class Models'
version: 0.1.1
doi: 10.32614/CRAN.package.CLCM
abstract: 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)
  <https://doi.org/10.5281/zenodo.22663151>.
authors:
- family-names: Iaconangelo
  given-names: Charlie
  email: charles.iaconangelo@gmail.com
repository: https://cjangelo.r-universe.dev
repository-code: https://github.com/CJangelo/CLCM
commit: b6a7bf324ef9962498fc1b9aa3bfac0f83c0dd2f
url: https://cjangelo.github.io/CLCM/
date-released: '2026-09-12'
contact:
- family-names: Iaconangelo
  given-names: Charlie
  email: charles.iaconangelo@gmail.com