grmcor: An R Package for Range-Restriction Bias Correction of Discrimination Parameters in the Graded Response Model

The Graded Response Model (GRM) is widely used for analyzing polytomous response data from attitude, personality, and character measurement instruments. However, when response data are collected from a range-restricted sample such as selected applicants, screened participants, or high-performing students, GRM discrimination parameters are systematically underestimated. No existing R package implements range-restriction bias correction specifically for GRM discrimination parameters. This paper introduces grmcor, an R package that implements the truncated normal standard deviation ratio correction for GRM discrimination parameters under direct range restriction. The package provides functions for estimating GRM parameters from restricted samples, applying the correction, comparing restricted and corrected estimates, visualizing bias patterns, and validating the correction procedure via Monte Carlo simulation. Monte Carlo results demonstrate that grmcor substantially reduces bias in discrimination parameter estimates, with mean bias reduced from -0.64 to near zero and RMSE reduced by approximately 52% under 50% range restriction. The package is freely available via GitHub.