mirtjml

Author: Siliang Zhang, Yunxiao Chen, Xiaoou Li
Contact: https://cran.r-project.org/web/packages/mirtjml/index.html
Description: Provides constrained joint maximum likelihood estimation algorithms for item factor analysis (IFA) based on multidimensional item response theory models. So far, we provide functions for exploratory and confirmatory IFA based on the multidimensional two parameter logistic (M2PL) model for binary response data. Comparing with traditional estimation methods for IFA, the methods implemented in this package scale better to data with large numbers of respondents, items, and latent factors. The computation is facilitated by multiprocessing 'OpenMP' API. For more information, please refer to: 1. Chen, Y., Li, X., & Zhang, S. (2018). Joint Maximum Likelihood Estimation for High-Dimensional Exploratory Item Factor Analysis. Psychometrika, 1-23.
Analyses: Interrater Reliability; Interrater Reliability; Rater Effects; Reliability; Sample size calculation for reliability
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, simulated dataset