STATISTICS
Linearity and measuring interval: a practical guide for biomedical scientists
In this fourth article in his current series, Stephen MacDonald moves on to provide a guide to dealing with the results of statistical tests initially that look reassuring yet still hide a clinically important problem.
The term linearity is a bit misleading. The instrument doesn’t need to produce a literal straight line internally, and many calibration curves are deliberately non-linear.
Every quantitative test has limits. Push a specimen too high or too low and the result stops behaving proportionally to the amount of measurand actually present. Signal saturation and reagent depletion blunt the response at the top end. Imprecision and detection capability limit it at the botom. Before a laboratory reports a number, it needs to know where that number can be trusted. Linearity studies are how we find out. The name is a bit misleading. The instrument doesn’t need to produce a literal straight line internally, and many calibration curves are deliberately non-linear. What matters is whether the final reported result stays acceptably proportional to concentration across the interval you intend to use. A pretty straight-looking graph, a correlation coefficient near 1, or a non-significant curvature test can all look reassuring and still hide a clinically important problem, which is really the point of this article.
Term
Direct measuring interval Extended reportable interval
What it means here
Interval measured without dilution or other pretreatment Wider interval reportable after a validated dilution procedure
Analytical measurement range (AMR) Common synonym for the direct interval Allowable deviation
Table 1. Terminology used throughout this article.
Predefined maximum acceptable departure from the expected linear response
Linearity, validation and verification – The essentials Linearity describes whether measured results stay proportional to the measurand’s true concentration across a stated interval. It is not the same as correlation (a high R² just means results generally rise with concentration – it says nothing about the size of local deviations), and it is not the same as trueness (a procedure can be perfectly linear and still
September 2026
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