Skip to content

Statistical Methods for Diagnostic Evaluation

This page explains the statistical methods used to evaluate diagnostic tests — in plain language, with the interpretation each method supports.

ROC Analysis

What it does: Plots sensitivity against (1 − specificity) across all possible cutoffs; the AUC (area under the curve) summarizes overall accuracy.

AUC Interpretation
> 0.9 Excellent
0.8–0.9 Good
0.7–0.8 Fair
< 0.7 Poor

ROC analysis also identifies the optimal cutoff — the threshold that best balances sensitivity and specificity for the clinical context.

Bland-Altman Plot

What it does: Plots the difference between two methods against their mean, visualizing bias (systematic difference) and limits of agreement.

  • A mean difference near zero → no systematic bias.
  • Narrow limits of agreement → the methods agree closely.

Passing-Bablok Regression

What it does: A non-parametric regression that estimates systematic bias (intercept ≠ 0) and proportional bias (slope ≠ 1) between two methods.

Result Meaning
Intercept ≠ 0 Constant (systematic) bias
Slope ≠ 1 Proportional bias (bias grows with concentration)

Confidence Intervals (95%)

What they do: Express the precision of an estimate. A sensitivity of "92% (95% CI 85–96%)" means the true sensitivity likely falls in that range — a wide interval signals a small or noisy study.

FAQ

Why use both Bland-Altman and Passing-Bablok? They answer different questions — Bland-Altman visualizes agreement, Passing-Bablok quantifies systematic and proportional bias. Together they give a complete picture.

What is a good AUC for a veterinary diagnostic test? Above 0.9 is excellent; 0.8–0.9 is good. For screening tests, prioritize sensitivity; for confirmatory tests, specificity.

For study designs, see Study Design.

Authored by: Migibio Clinical & Scientific Affairs, Guangzhou Magic Biotech Co., Ltd.

Reviewed by: Migibio R&D Quality Committee

Last updated: 2026-08-13

Disclosure: Migibio (Guangzhou Magic Biotech Co., Ltd.) is the manufacturer of the FIA680/FIA880 analyzers and FICT reagents referenced in this content. See our Editorial & Review Policy.

Contact: Martin.Wong  ·  Phone (WhatsApp): +86 13323237275  ·  Email: [email protected]
Back to top