Cognitive Diagnostic Computerized Adaptive Testing

Provides a set of functions for conducting cognitive diagnostic computerized adaptive testing applications (Chen, 2009) ). It includes different item selection rules such us the global discrimination index (Kaplan, de la Torre, and Barrada (2015) ) and the nonparametric selection method (Chang, Chiu, and Tsai (2019) ), as well as several stopping rules. Functions for generating item banks and responses are also provided. To guide item bank calibration, model comparison at the item level can be conducted using the two-step likelihood ratio test statistic by Sorrel, de la Torre, Abad and Olea (2017) .

cdcatR: Cognitive Diagnostic Computerized Adaptive Testing in R

How to cite the package

Sorrel, M.A., Nájera, P., and Abad, F.J. (2021). cdcatR: Cognitive Diagnostic Computerized Adaptive Testing in R. R package version 1.0.6 Retrieved from https://cran.r-project.org/package=cdcatR.

Features of the package

• Conducting CD-CAT applications in R
• Comparing different CD-CAT applications in terms of classification accuracy and CAT length

Installation

A stable version of cdcatR is available at CRAN and can be installed using:

install.packages("cdcatR")

To install this package from source:

1. Windows users may need to install the Rtools and include the checkbox option of installing Rtools to their path for easier command line usage. Mac users will have to download the necessary tools from the Xcode and its related command line tools (found within Xcode's Preference Pane under Downloads/Components); most Linux distributions should already have up to date compilers (or if not they can be updated easily).
2. Install the remotes package (if necessary), and install the package from the Github source code.

#install.packages("remotes")
remotes::install_github("miguel-sorrel/cdcatR")