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. (2021) .

ohoegdm

The goal of ohoegdm is to provide an implementation of the Ordinal Higher-order Exploratory General Diagnostic Model for Polytomous Data as described by Culpepper and Balamuta (2023).

Installation

You can install the released version of ohoegdm from CRAN with:

install.packages("ohoegdm")

Or, you can be on the cutting-edge development version on GitHub using:

# install.packages("devtools")
devtools::install_github("tmsalab/ohoegdm")

Usage

To use ohoegdm, load the package using:

library("ohoegdm")

From here, the OHO-EGDM model can be estimated using:

my_model = ohoegdm::ohoegdm(
  y = <data>,
  k = <k>,
  m = <item-responses-categories>,
  order = <model-interaction-order>
)

Authors

Steven Andrew Culpepper and James Joseph Balamuta

Citing the ohoegdm package

To ensure future development of the package, please cite ohoegdm package if used during an analysis or simulation study. Citation information for the package may be acquired by using in R:

citation("ohoegdm")

License

GPL (>= 2)