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A simple method for evaluating data from an interlaboratory study

W Horwitz1, P Britton, S J Chirtel

  • 1U.S. Food and Drug Administration, Washington, DC 20204, USA.

Journal of AOAC International
|December 16, 1998
PubMed
Summary
This summary is machine-generated.

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The HORRAT ratio offers a simple method to evaluate laboratory performance in chemical analysis. This approach helps identify and address issues in methods and laboratory procedures for improved accuracy.

Area of Science:

  • Analytical Chemistry
  • Environmental Science
  • Laboratory Science

Background:

  • Evaluating large-scale laboratory performance is crucial for method validation.
  • Traditional outlier detection can be complex and time-consuming.
  • The Horwitz equation provides a theoretical basis for expected precision.

Purpose of the Study:

  • To introduce and validate the HORRAT ratio as a straightforward metric for assessing laboratory and method performance.
  • To apply the HORRAT ratio to existing data from U.S. Environmental Protection Agency (EPA) method 245.1 for mercury analysis.
  • To compare the HORRAT method with traditional outlier removal techniques.

Main Methods:

  • Calculating the HORRAT ratio by dividing experimental among-laboratories relative standard deviation by the Horwitz formula's relative standard deviation.

Related Experiment Videos

  • Setting action limits for HORRAT (approx. 1.0 +/- 0.5 for acceptable, > approx. 2.0 for review).
  • Iteratively removing extreme values and re-evaluating the HORRAT ratio.

    • Main Results:

    • The HORRAT ratio provides a simple, effective method for evaluating laboratory performance without complex statistical tables.
    • Application to EPA method 245.1 showed comparable method-performance parameters to robust biweight outlier removal.
    • The HORRAT method achieved a fourfold improvement in precision compared to the original study, albeit with more rejected experimental values.

    Conclusions:

    • The HORRAT ratio is a practical and effective tool for assessing the performance of analytical methods across multiple laboratories.
    • It aids in identifying laboratories or methods requiring procedural review and improvement.
    • The method offers a simpler alternative to complex statistical outlier analysis for routine performance monitoring.