Package: discnorm 0.2.1

Njål Foldnes

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>.

Authors:Njål Foldnes [aut, cre], Steffen Grønneberg [aut]

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NEWS

# Install 'discnorm' in R:
install.packages('discnorm', repos = 'https://cloud.r-project.org')

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 205 downloads 2 exports 30 dependencies

Last updated 3 years agofrom:a27fbe03d5. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 21 2025
R-4.5-linuxOKMar 21 2025
R-4.4-linuxOKMar 21 2025

Exports:bootTestcatLSadj

Dependencies:ADGofTestadmiscarulesCDMcolorspacecopulacubaturegenericsGoFKernelgslKernSmoothlatticelavaanMASSMatrixmnormtmvtnormnumDerivpbapplypbivnormpbvpcaPPpolycorpsplinequadprogRcppRcppArmadillosirtstabledistTAM

Discnorm: Detecting and adjusting for underlying non-normality in ordinal datasets

Njål Foldnes and Steffen Grønneberg

Rendered fromdiscnormvignette.Rmdusingknitr::rmarkdownon Mar 21 2025.

Last update: 2022-03-22
Started: 2020-05-20

Citation

To cite covsim in publications use:

Njål Foldnes, Steffen Grønneberg (2019). Pernicious Polychorics: The Impact and Detection of Underlying Non-normality. Structural Equation Modeling: A Multidisciplinary Journal. URL https://doi.org/10.1080/10705511.2019.1673168

Corresponding BibTeX entry: 

  @Article{,
    title = {Pernicious Polychorics: The Impact and Detection of
      Underlying Non-normality},
    author = {Njål Foldnes and Steffen Grønneberg},
    journal = {Structural Equation Modeling: A Multidisciplinary
      Journal},
    year = {2019},
    url = {https://doi.org/10.1080/10705511.2019.1673168},
  }

Readme and manuals

discnorm

This package contains an implementation of a the bootstrap test for underlying non-normality proposed by Foldnes and Gronneberg (Structural Equation Modeling, 2019). Also contains an adjusted polychoric estimator proposed by Gronneberg and Foldnes (Psychological Methods, 2022).

How to install

You can install:

  • the stable release on CRAN:

    install.packages("discnorm")

  • the latest development version:

    devtools::install_github("njaalf/discnorm")

Package overview

The package offers function bootTest() which tests an ordinal data frame for underlying normality. A function catLSadj() is provided that computes the adjusted polychoric correlations based on user-provided non-normal marginals.

References

Njål Foldnes & Steffen Grønneberg (2019) Pernicious Polychorics: The Impact and Detection of Underlying Non-normality, Structural Equation Modeling: A Multidisciplinary Journal, DOI: 10.1080/10705511.2019.1673168

Steffen Grønneberg & Njål Foldnes (2022) Factor Analyzing Ordinal Items Requires Substantive Knowledge of Response Marginals, Psychological Methods, DOI: 10.1037/met0000495