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.html , discnorm.pdf
Vignettes:	Discnorm: Detecting and adjusting for underlying non-normality in ordinal datasets (source, R code)

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:

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