MAT

Author: Seung W. Choi & David R. King
Contact: https://cran.r-project.org/web/packages/MAT/
Description: Multidimensional adaptive testing (MAT) is ideal for testing situations that require the estimation of two or more distinct, albeit correlated latent abilities. MAT offers a number of advantages over unidimensional adaptive testing, such as more adequate coverage of content (Segall,1996), increased measurement efficiency for variable-length tests (Segall, 1996), and increased measurement precision for fixed-length tests (Wang, Chen, & Cheng, 2004). Simulation of MAT on both empirical and generated data is useful for developing computerized adaptive testing (CAT) systems and for teaching the principles of MAT.
Analyses: diagnostics from MCMC output
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: guide in pdf