Diagnostics › Method comparison

Precision & trueness verification

Verifies that an assay's observed precision and bias meet the manufacturer's claims, using a one-sided chi-square for imprecision and a bias test for trueness.

What is Precision & trueness verification?

When you bring an assay in-house you don't re-establish its performance from scratch — you verify the manufacturer's claims on a smaller sample. Two claims matter: is my imprecision no worse than claimed, and is my bias within the allowable limit (trueness).

Imprecision is verified with a one-sided upper chi-square test: given the claimed SD, the observed SD is acceptable unless it is significantly larger. Trueness is verified by comparing the observed mean to the claimed/target value (a paired-t or difference against an allowable bias). This mirrors the CLSI EP15 user-verification protocol.

When should I use Precision & trueness verification?

  • User verification of a new assay, lot, or instrument against the manufacturer's precision/bias claims.
  • Periodic re-verification of established methods.

What data does it need?

A column of measurements on a known material, plus the claimed SD (for precision), the claimed/target mean (for trueness), and an allowable bias.

What does it report?

The precision verdict (observed vs claimed SD, chi-square) and the trueness verdict (observed bias vs the claim, with p-value).

What does it assume?

  • Measurements come from a stable, in-control run of the material.
  • Approximately normal data.

Formula

Precision: χ² = (n−1)·s² / σ₀² vs χ²_{0.95, n−1} (verified when not significantly larger)
Trueness: |mean − claimed| ≤ allowable bias

How do I interpret the result?

"Not verified" on precision means your SD is significantly worse than claimed — investigate before use. Because verification uses few replicates, a pass is reassurance rather than proof; a borderline fail may reflect low power, so consider more replicates before rejecting the method.

See also

References

  • CLSI EP15-A3. User Verification of Precision and Estimation of Bias.