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aiEvalR  

Statistical and Psychometric Evaluation of AI Systems
View on CRAN: Click here


Download and install aiEvalR package within the R console
Install from CRAN:
install.packages("aiEvalR")

Install from Github:
library("remotes")
install_github("cran/aiEvalR")

Install by package version:
library("remotes")
install_version("aiEvalR", "0.1.0")



Attach the package and use:
library("aiEvalR")
Maintained by
Subir Hait
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-30
Latest Update: 2026-08-30
Description:
Evaluates artificial intelligence (AI) systems as measurement instruments using psychometric methods. Provides multi-facet generalizability theory (G-study and D-study) via 'lme4', reliability via the intraclass correlation coefficient (ICC), calibration via the expected calibration error (ECE) and Brier score, robustness stress testing, and group disparity diagnostics. Item-level differential item functioning (DIF) based on item response theory (IRT) is delegated to the 'aiDIF' package. Methods follow Cronbach, Gleser, Nanda and Rajaratnam (1972, <ISBN:9780471188506>) and Brennan (2001) <doi:10.1007/978-1-4757-3456-0>.
How to cite:
Subir Hait (2026). aiEvalR: Statistical and Psychometric Evaluation of AI Systems. R package version 0.1.0, https://cran.r-project.org/web/packages/aiEvalR. Accessed 24 Oct. 2026.
Previous versions and publish date:
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Full aiEvalR package functions and examples
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