Bayesian Estimation of an Exploratory Deterministic Input, Noisy and Gate Model

Perform a Bayesian estimation of the exploratory deterministic input, noisy and gate (EDINA) cognitive diagnostic model described by Chen et al. (2018) .

edina

Perform a Bayesian estimation of the Exploratory Deterministic Input, Noisy “And” Gate (EDINA) cognitive diagnostic model described by Chen et al. (2018).

Installation

You can install edina from CRAN using:

install.packages("edina")

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

if(!requireNamespace("remotes")) install.packages("remotes")
remotes::install_github("tmsalab/edina")

Usage

To use the edina package, load it into R using:

library("edina")

From there, the EDINA model can be estimated using:

edina_model = edina(<data>, chain_length = 10000)

To compute a model underneath different K attribute configured Q matrices, use:

edina_model = auto_edina(<data>, k = 2:4, chain_length = 10000)

Note: Higher K configured Q matrices take longer to estimate.

Authors

James Joseph Balamuta, Steven Andrew Culpepper, and Jeffrey A. Douglas

Citing the edina package

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

citation("edina")

License

GPL (>= 2)