edm

The goal of edm is to provide a modeling framework for exploratory diagnostic models and classical diagnostic models.

Installation

The edm package is currently only available via GitHub. To install edm, your computer will need to have a compiler. The following guides are avaliable:

• Windows: Rtools
• macOS: Rtools

From there, please use devtools to retrieve the latest development version.

if(!requireNamespace("remotes", quietly = TRUE)) install.packages("remotes")
remotes::install_github("tmsalab/edm")

Usage

Load the edm package into R:

library(edm)

Exploratory CDM models can be estimated with:

edina_model = edina(<data>, <k>)
errum_model = errum(<data>, <k>, ... )

Classical CDMs can be estimated using:

dina_model = dina(<data>, <q>)
rrum_model = rrum(<data>, <q>)

Details

The edm package is designed to act more as a “virtual” package. The main functionalities of edm are split across multiple packages. The rationale for this is many areas of psychometrics have overlap in terms of computational code used. By dividing the underlying source of the edm package, we are enabling fellow psychometricians to be able to incorporate established routines into their own code. In addition, we are lowering the amount of redundancies, or copy and pasted code, within the CDM framework we are building.

Specifically, the edm package imports estimation routines from:

• dina: Estimating the Deterministic Input, Noisy “And” Gate (‘DINA’) cognitive diagnostic model parameters using a Gibbs sampler.
• edina: Estimating the Exploratory Deterministic Input, Noisy “And” Gate (‘EDINA’) cognitive diagnostic model parameters using a Gibbs sampler.
• rrum: Estimating the reduced Reparametrized Unified Model (‘rRUM’) with a Gibbs sampler.
• errum: Estimating the Exploratory reduced Reparametrized Unified Model (‘ErRUM’) with a Gibbs sampler.

Moreover, we have additional packages that are used within the modeling process:

• rgen: Simulate Multivariate Probability Distributions
• simcdm: Simulate responses underneath a DINA or rRUM model.
• shinyedm: User Interface for Modeling with Exploratory Models

Lastly, we have sampled data packages available here:

• edmdata: Data package containing psychometric modeling data used in multiple packages.

Authors

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

Citing the edm package

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

citation("edm")

License

GPL (>= 2)