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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "grassr" in publications use:'
type: software
license: MIT
title: 'grassr: Context-Conditioned Reporting for Binary Rater Reliability'
version: 0.6.2
identifiers:
- type: doi
  value: 10.32614/CRAN.package.grassr
abstract: Generates a Report Card for rater reliability on binary outcomes from an
  N x k subject-by-rater rating matrix, on both the inter-rater and intra-rater axes.
  Each panel coefficient (PABAK, Gwet's AC1, Fleiss' kappa, and observed intraclass
  correlation) is positioned on a simulation-calibrated reference surface conditioned
  on the study's rater count, sample size, and prevalence, yielding a surface-position
  percentile with a bootstrap confidence qualifier. A cross-coefficient discordance
  diagnostic (delta-hat), with per-design thresholds calibrated to fixed false-positive
  rates, flags panels for which no single coefficient is a stable summary; for such
  divergent panels the report routes to a pairwise PABAK matrix and per-rater sensitivity
  and specificity recovered from a Dawid-Skene latent-class fit (Hui-Walter bounds
  at k = 2).
authors:
- family-names: Semmel
  given-names: Austin
  email: austinsemmel@gmail.com
- family-names: Gidaro
  given-names: Rachel
preferred-citation:
  type: manual
  title: 'grassr: Context-Conditioned Reporting for Binary Rater Reliability'
  authors:
  - family-names: Semmel
    given-names: Austin
    email: austinsemmel@gmail.com
  - family-names: Gidaro
    given-names: Rachel
  year: '2026'
  notes: R package version 0.6.1
  url: https://github.com/defense031/grassr
repository: https://defense031.r-universe.dev
repository-code: https://github.com/defense031/grassr
commit: d66f4b38f51acc6967574c9ccf12444ea0019639
url: https://defense031.github.io/grassr/
date-released: '2026-07-09'
contact:
- family-names: Semmel
  given-names: Austin
  email: austinsemmel@gmail.com