Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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✓Committers with academic emails
1 of 4 committers (25.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.5%) to scientific vocabulary
Repository
Polytomous Variable Latent Class Analysis (R package)
Basic Info
- Host: GitHub
- Owner: dlinzer
- Language: R
- Default Branch: master
- Homepage: https://dlinzer.github.io/poLCA/
- Size: 1000 KB
Statistics
- Stars: 54
- Watchers: 12
- Forks: 19
- Open Issues: 18
- Releases: 0
Metadata Files
README.md
poLCA
Polytomous Variable Latent Class Analysis
poLCA is a software package for the estimation of latent class models and latent class regression models for polytomous outcome variables, implemented in the R statistical computing environment.
Latent class analysis (also known as latent structure analysis) can be used to identify clusters of similar "types" of individuals or observations from multivariate categorical data, estimating the characteristics of these latent groups, and returning the probability that each observation belongs to each group. These models are also helpful in investigating sources of confounding and nonindependence among a set of categorical variables, as well as for density estimation in cross-classification tables. Typical applications include the analysis of opinion surveys; rater agreement; lifestyle and consumer choice; and other social and behavioral phenomena.
The basic latent class model is a finite mixture model in which the component distributions are assumed to be multi-way cross-classification tables with all variables mutually independent. The model stratifies the observed data by a theoretical latent categorical variable, attempting to eliminate any spurious relationships between the observed variables. The latent class regression model makes it possible for the researcher to further estimate the effects of covariates (or "concomitant" variables) on predicting latent class membership.
poLCA uses expectation-maximization and Newton-Raphson algorithms to find maximum likelihood estimates of the parameters of the latent class and latent class regression models.
Package authors
Installation
To install the package directly through R, type
R
install.packages("poLCA", dependencies = TRUE)
and select a CRAN mirror. Once the installation is complete, enter
R
library(poLCA)
to load the package into memory for use.
poLCA is distributed through the Comprehensive R Archive Network, CRAN. The compiled package source and MacOS and Windows binary files can be downloaded from https://cran.r-project.org/web/packages/poLCA.
The poLCA package appears in CRAN Task Views for Cluster Analysis & Finite Mixture Models, and Psychometric Models and Methods. poLCA is provided free of charge, subject to version 2 of the GPL or any later version.
Documentation
Download user's manual (PDF). The package is also documented internally upon installation. For help in R, type
R
?poLCA
Citation
Users of poLCA are requested to cite the software package as:
Linzer, Drew A. and Jeffrey Lewis. 2022. "poLCA: Polytomous Variable Latent Class Analysis." R package version 1.6. https://dlinzer.github.com/poLCA.
and
Linzer, Drew A. and Jeffrey Lewis. 2011. "poLCA: an R Package for Polytomous Variable Latent Class Analysis." Journal of Statistical Software. 42(10): 1-29. https://www.jstatsoft.org/v42/i10
Contact
Please direct all inquiries, comments, and reports of bugs to drew@votamatic.org.
Owner
- Name: Drew Linzer
- Login: dlinzer
- Kind: user
- Website: http://votamatic.org
- Repositories: 3
- Profile: https://github.com/dlinzer
GitHub Events
Total
- Watch event: 5
- Issue comment event: 1
- Fork event: 2
Last Year
- Watch event: 5
- Issue comment event: 1
- Fork event: 2
Committers
Last synced: almost 3 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Drew Linzer | d****r@g****m | 15 |
| Jeff | j****s@u****u | 3 |
| Drew Linzer | d****w@v****g | 2 |
| Claudio Bustos | c****s@g****m | 2 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 12 months ago
All Time
- Total issues: 13
- Total pull requests: 11
- Average time to close issues: almost 2 years
- Average time to close pull requests: about 2 months
- Total issue authors: 9
- Total pull request authors: 6
- Average comments per issue: 0.92
- Average comments per pull request: 0.36
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- mikebarkmin (5)
- Blanch-Font (1)
- DaniMori (1)
- dchiu911 (1)
- zh-zhang1984 (1)
- amyclairet (1)
- adamSales (1)
- wwloh (1)
- mkleinsa (1)
Pull Request Authors
- mikebarkmin (5)
- JeffreyBLewis (2)
- matt5mitchell (1)
- Gootjes (1)
- daob (1)
- clbustos (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 2
-
Total downloads:
- cran 5,713 last-month
- Total docker downloads: 44,221
-
Total dependent packages: 10
(may contain duplicates) -
Total dependent repositories: 35
(may contain duplicates) - Total versions: 13
- Total maintainers: 1
cran.r-project.org: poLCA
Polytomous Variable Latent Class Analysis
- Homepage: https://github.com/dlinzer/poLCA
- Documentation: http://cran.r-project.org/web/packages/poLCA/poLCA.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
-
Latest release: 1.6.0
published over 4 years ago
Rankings
Maintainers (1)
conda-forge.org: r-polca
- Homepage: http://dlinzer.github.com/poLCA
- License: GPL-2.0-or-later
-
Latest release: 1.6.0
published over 4 years ago
Rankings
Dependencies
- MASS * depends
- scatterplot3d * depends