Description
Ordinal Higher-Order Exploratory General Diagnostic Model for Polytomous Data.
Description
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>.
README.md
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 (In Press).
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)