Individual skill
diagnostic-test-accuracy
Evaluating diagnostic tests — sensitivity, specificity, ROC analysis, likelihood ratios, and study design.
skills/diagnostic-test-accuracy/SKILL.md
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## Overview
diagnostic-test-accuracy covers how to evaluate whether a test distinguishes disease from
non-disease: study designs (cohort, case-control, with their biases), the core metrics
(sensitivity, specificity, predictive values, likelihood ratios, ROC/AUC), and the reporting
standards (STARD) that make accuracy studies credible. A test's accuracy in a paper and its
usefulness in practice are different things — this skill keeps both in view.
## When to use
- Designing a diagnostic accuracy study: population, reference standard, blinding.
- Computing and interpreting sensitivity, specificity, PPV/NPV, likelihood ratios.
- ROC analysis and AUC: what it means, when it misleads.
- Choosing cutoffs: Youden index, clinical utility, net benefit.