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Effectively simulates the discretization process inherent to Likert scales while minimizing distortion. It converts continuous latent variables into ordinal categories to generate Likert scale item responses. Particularly useful for accurately modeling and analyzing survey data that use Likert scales, especially when applying statistical techniques that require metric data.
Version: | 1.2.1 |
Depends: | R (≥ 3.5) |
Imports: | graphics, mvtnorm, sn, stats, utils |
Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
Published: | 2024-06-24 |
DOI: | 10.32614/CRAN.package.latent2likert |
Author: | Marko Lalovic [aut, cre] |
Maintainer: | Marko Lalovic <marko at lalovic.io> |
BugReports: | https://github.com/markolalovic/latent2likert/issues/ |
License: | MIT + file LICENSE |
URL: | https://lalovic.io/latent2likert/ |
NeedsCompilation: | no |
Language: | en-US |
Materials: | README NEWS |
CRAN checks: | latent2likert results |
Reference manual: | latent2likert.pdf |
Vignettes: |
Using latent2likert |
Package source: | latent2likert_1.2.1.tar.gz |
Windows binaries: | r-devel: latent2likert_1.2.1.zip, r-release: latent2likert_1.2.1.zip, r-oldrel: not available |
macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): latent2likert_1.2.1.tgz, r-release (x86_64): latent2likert_1.2.1.tgz, r-oldrel (x86_64): latent2likert_1.2.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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