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discnorm: Test for Discretized Normality in Ordinal Data

Tests whether multivariate ordinal data may stem from discretizing a multivariate normal distribution. The test is described by Foldnes and Grønneberg (2019) <doi:10.1080/10705511.2019.1673168>. In addition, an adjusted polychoric correlation estimator is provided that takes marginal knowledge into account, as described by Grønneberg and Foldnes (2022) <doi:10.1037/met0000495>.

Version: 0.2.1
Imports: lavaan (≥ 0.6.10), arules, sirt, MASS, pbivnorm, cubature, copula, mnormt, GoFKernel
Suggests: knitr, rmarkdown
Published: 2022-05-25
DOI: 10.32614/CRAN.package.discnorm
Author: Njål Foldnes [aut, cre], Steffen Grønneberg [aut]
Maintainer: Njål Foldnes <njal.foldnes at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: discnorm citation info
Materials: README NEWS
CRAN checks: discnorm results

Documentation:

Reference manual: discnorm.pdf
Vignettes: Discnorm: Detecting and adjusting for underlying non-normality in ordinal datasets

Downloads:

Package source: discnorm_0.2.1.tar.gz
Windows binaries: r-devel: discnorm_0.2.1.zip, r-release: discnorm_0.2.1.zip, r-oldrel: discnorm_0.2.1.zip
macOS binaries: r-release (arm64): discnorm_0.2.1.tgz, r-oldrel (arm64): discnorm_0.2.1.tgz, r-release (x86_64): discnorm_0.2.1.tgz, r-oldrel (x86_64): discnorm_0.2.1.tgz
Old sources: discnorm archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=discnorm to link to this page.

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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