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LCPA

1.0.2

A General Framework for Latent Classify and Profile Analysis

0packages depend
2.7Kdownloads / year
0.1%test coverage
13/13checks pass

Overview

About
Maintained by Haijiang QinFirst published 2026-01-223 releasesCRAN page ↗

A unified latent class modeling framework that encompasses both latent class analysis (LCA) and latent profile analysis (LPA), offering a one-stop solution for latent class modeling. It implements state-of-the-art parameter estimation methods, including the expectation–maximization (EM) algorithm, neural network estimation (NNE; requires users to have 'Python' and its dependent libraries installed on their computer), and integration with 'Mplus' (requires users to have 'Mplus' installed on their computer). In addition, it provides commonly used model fit indices such as the Akaike information criterion (AIC) and Bayesian information criterion (BIC), as well as classification accuracy measures such as entropy. The package also includes fully functional likelihood ratio tests (LRT) and bootstrap likelihood ratio tests (BLRT) to facilitate model comparison, along with bootstrap-based and observed information matrix-based standard error estimation. Furthermore, it supports the standard three-step approach for LCA, LPA, and latent transition analysis (LTA) with covariates, enabling detailed covariate analysis. Finally, it includes several user-friendly auxiliary functions to enhance interactive usability.

Install

Health

CRAN checks
13OK
Slowest check: 6.3 min · r-devel-windows-x86_64
Code health
Yes
Tests · ratio 0.02
0.1%
Coverage · measured lines
100%
Documentation · exports
16
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-04-22
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-18
    13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
77%
Documented parameters
100%
Return-value docs
100%
References docs
28%

Downloads

2.7K
CRAN downloads in the past year
Rank #8,861 · ~7/day · ~222/mo
Daily download trend is not available in this view yet.
23130 days
1K90 days
2.7K1 year
Compare downloads with other packages →
Also on250 r2u18 autocran

Dependencies

Declared dependencies
16 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.1.0
LinkingTo (2)
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (2)
Maintainer (1)
Author, Maintainer, Copyright holder
Authors (2)
Author, Maintainer, Copyright holder
Author, Copyright holder
Copyright holders (2)
Author, Maintainer, Copyright holder
Author, Copyright holder
Package Timeline

3 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.2Latest
    2026-04-10 · current release · diff ↗
  • 1.0.1
    2026-02-27 · diff ↗
  • 1.0.0
    2026-01-22
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-01-22
Total releases
3 / 1 yrs
License
GPL-3 OSI
Minimum R
≥ 4.1.0
Download size
229 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("LCPA")
Qin, H., & Guo, L. (2026). LCPA: A General Framework for Latent Classify and Profile Analysis (Version 1.0.2) [Computer software]. https://doi.org/10.32614/CRAN.package.LCPA

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for LCPA version 1.0.2 [Data set]. HJJB, LLC. Data release v2026-08-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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