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A Tool for Agreement and Alignment Analysis in Binary Rating Tasks: The R Package scindex
1Faculty of Education, Free University of Bolzano-Bozen, Bressanone-Brixen (BZ), Italy.
Applied Psychological Measurement
|July 2, 2026
Summary
The scindex R package enhances inter-rater reliability analysis for binary classification. It calculates key metrics like Cohen's κ, Fleiss' κ, and signal detection parameters for robust assessment.
Area of Science:
- Statistics
- Biostatistics
- Psychometrics
Background:
- Inter-rater reliability is crucial for consistent diagnostic and classification tasks.
- Existing methods may not fully capture the nuances of rater agreement and response criteria.
Purpose of the Study:
- To introduce scindex, an R package for comprehensive inter-rater reliability analysis.
- To provide tools for calculating established reliability metrics and novel convergence measures.
Main Methods:
- The scindex package computes Cohen's kappa and Fleiss' kappa.
- It estimates signal detection theory parameters (sensitivity, specificity, decision thresholds) using ground-truth labels.
- The Strategic Convergence Index (SCI) is implemented to assess rater response criteria convergence.
Main Results:
- scindex offers a unified framework for analyzing inter-rater reliability in binary classification.
- The package facilitates the estimation of both agreement levels and underlying decision-making processes.
- The Strategic Convergence Index provides a novel approach to evaluating rater consistency.
Conclusions:
- scindex is a valuable tool for researchers and practitioners needing to assess inter-rater reliability.
- The package enhances the analysis of binary classification tasks by integrating multiple statistical measures.
- Utilizing scindex can lead to more reliable and interpretable results in classification studies.
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