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Running intraclass correlation coefficient (icc) reliability analysis analysis...
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Analyze another fileMeasures inter-rater reliability — how much raters agree when scoring the same subjects. ICC values near 1 mean excellent agreement; below 0.5 is poor.
Use this when multiple raters scored the same items and you want to quantify their consistency.
If you're comparing group means (not rater agreement), use ANOVA.
Built for: Researcher, psychometrician, quality analyst, clinical trialist
Typical data source: Rating data with multiple raters scoring the same subjects
Rater agreement data
Minimum 10 rows · Best with 30-500 subjects
Measures inter-rater reliability using ICC to assess agreement and consistency among multiple raters scoring subjects on continuous scales. Computes all 10 ICC forms, stratified ICC by subgroups, rater bias analysis, and Bland-Altman agreement plots.
Primary ICC result with confidence interval and interpretation
All 10 ICC forms with 95% confidence intervals
Pairwise correlations between all raters
Per-rater statistics showing means, variability, and systematic bias
Agreement plot showing limits of agreement between rater pairs
Actionable recommendations for improving inter-rater reliability
Plain-English interpretation — what the numbers mean, what's significant, and what to do next.
Need something simpler? Correlation — Just want pairwise correlations between raters
Need more power? Ancova — Need to control for rater effects in a treatment study
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data — validated R analyses, interactive reports, AI insights, and PDF export.
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