Purpose

This section documents the data preprocessing pipeline for the inter-rater reliability study. Perfect data retention (100%) indicates no observations were excluded during cleaning, which is critical for maintaining the integrity of ICC calculations and ensuring all 120 subjects with 5 raters each are represented in the final analysis.

Key Findings

Retention Rate: 100% (600/600 rows) - All observations passed quality checks with zero exclusions
Rows Removed: 0 - No data loss occurred during preprocessing
Train/Test Split: Not applicable - This is a reliability assessment, not a predictive model requiring data partitioning
Data Integrity: Complete dataset preserved ensures ICC estimates reflect the full sample without selection bias

Interpretation

The perfect retention rate demonstrates exceptionally clean input data with no missing values, duplicates, or invalid entries requiring removal. This is particularly important for ICC(2,k) calculations, which depend on balanced designs across all raters and subjects. The absence of any filtering or exclusion criteria means the reported ICC of 0.854 and stratified reliability estimates are based on the complete intended sample, strengthening confidence in the inter-rater reliability conclusions across all four diagnostic categories.

Context

No train/test split was applied because this analysis assesses measurement agreement rather than predictive performance. The 100% retention aligns with the study design of