grassr-package: grassr: Context-Conditioned Reporting for Binary Rater...

In grassr: Context-Conditioned Reporting for Binary Rater Reliability

grassr: Context-Conditioned Reporting for Binary Rater Reliability

Description

Generates a Report Card for rater reliability on binary outcomes from an N x k subject-by-rater rating matrix. Each panel coefficient is positioned on a simulation-calibrated reference surface conditioned on the study's rater count, sample size, and prevalence; a cross-coefficient discordance diagnostic (delta-hat) flags panels for which no single coefficient is a stable summary. The package implements the GRASS framework (Guide for Rater Agreement under Structural Skew).

Entry points

• grass_report() – the Report Card: coefficient panel, surface percentiles, delta-hat flag, and divergent-path routing

• position_on_surface() – position one observed coefficient on its calibrated reference surface

• pairwise_agreement() – pairwise PABAK matrix on the k = 2 surface

• latent_class_fit() – per-rater sensitivity/specificity via Dawid-Skene (Hui-Walter bounds at k = 2)

• grass_compute() – raw metric panel from 2x2 or rater data

• plot_surface() – plot an observed coefficient against its surface

Roadmap

See grass_roadmap for the framework taxonomy and the planned ordinal / multirater / continuous families.

Author(s)

Maintainer: Austin Semmel [e-mail]

Authors:

• Rachel Gidaro

See Also

Useful links:

• https://defense031.github.io/grassr/

• https://github.com/defense031/grassr

• Report bugs at https://github.com/defense031/grassr/issues

grassr documentation built on Sept. 22, 2026, 5:08 p.m.