ohoegdm: Ordinal Higher-Order Exploratory General Diagnostic Model for Polytomous Data

Perform a Bayesian estimation of the ordinal exploratory Higher-order General Diagnostic Model (OHOEGDM) for Polytomous Data described by Culpepper, S. A. and Balamuta, J. J. (In Press) <doi:10.1080/00273171.2021.1985949>.

Version: 0.1.0
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: edmdata, covr
Published: 2022-02-24
Author: Steven Andrew Culpepper ORCID iD [aut, cph], James Joseph Balamuta ORCID iD [aut, cre, cph]
Maintainer: James Joseph Balamuta <balamut2 at illinois.edu>
BugReports: https://github.com/tmsalab/ohoegdm/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/tmsalab/ohoegdm, https://tmsalab.github.io/ohoegdm/
NeedsCompilation: yes
Citation: ohoegdm citation info
Materials: README NEWS
In views: Psychometrics
CRAN checks: ohoegdm results

Documentation:

Reference manual: ohoegdm.pdf

Downloads:

Package source: ohoegdm_0.1.0.tar.gz
Windows binaries: r-devel: ohoegdm_0.1.0.zip, r-release: ohoegdm_0.1.0.zip, r-oldrel: ohoegdm_0.1.0.zip
macOS binaries: r-release (arm64): ohoegdm_0.1.0.tgz, r-oldrel (arm64): ohoegdm_0.1.0.tgz, r-release (x86_64): ohoegdm_0.1.0.tgz, r-oldrel (x86_64): ohoegdm_0.1.0.tgz

Linking:

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