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Comparing methods of measurements

J Ludbrook1

  • 1University of Melbourne Department of Surgery, Royal Melbourne Hospital, Parkville, Victoria, Australia.

Clinical and Experimental Pharmacology & Physiology
|February 1, 1997
PubMed
Summary
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Comparing measurement methods requires detecting systematic differences, not similarities. Least products regression is a sensitive technique for identifying fixed and proportional bias between methods, outperforming difference analysis.

Area of Science:

  • Biostatistics
  • Measurement Science
  • Clinical Research Methodology

Background:

  • Comparing two measurement methods for biological variables aims to identify systematic differences.
  • Systematic disagreement can arise from fixed bias (constant difference) or proportional bias (difference proportional to the measured value).
  • Both measurement methods and biological variation introduce random error into results.

Purpose of the Study:

  • To compare methods for measuring continuous biological variables.
  • To identify and distinguish between fixed and proportional bias in measurement methods.
  • To evaluate the suitability of different statistical techniques for method comparison.

Main Methods:

  • Pearson product-moment correlation coefficient (r) is insufficient for detecting systematic bias.

Related Experiment Videos

  • Least squares (Model I) regression is inappropriate when both variables have random error.
  • Model II regression, specifically least products regression, is suitable for data with random error in both variables.
  • Examination of differences between methods is an alternative bias detection approach.

    • Main Results:

    • Least products regression is preferred for Model II cases, minimizing the product of deviations.
    • This technique effectively calibrates one method against another.
    • Least products regression is sensitive for detecting and differentiating fixed and proportional bias.
    • Difference examination methods do not distinguish between fixed and proportional bias.

    Conclusions:

    • Least products regression is a superior technique for method comparison over difference examination.
    • This method accurately detects and distinguishes between fixed and proportional bias.
    • Accurate bias detection is crucial for reliable biological variable measurement.