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Additive, multiplicative, and mixed analytical errors

M Werner, S H Brooks, L B Knott

    Clinical Chemistry
    |November 1, 1978
    PubMed
    Summary
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    Analytical errors in laboratory methods are often mixed, not purely additive or multiplicative. Blinding quality control systems can increase multiplicative errors, impacting overall accuracy in clinical assays.

    Area of Science:

    • Clinical Chemistry
    • Analytical Chemistry
    • Laboratory Medicine

    Background:

    • Analytical errors in laboratory assays can be classified as additive or multiplicative based on their relationship with analyte concentration.
    • Understanding the error properties of complex, multi-step analytical methods is crucial for accurate diagnostic testing.
    • Quality control (QC) systems are essential for monitoring assay performance and ensuring reliable results.

    Purpose of the Study:

    • To determine if overall analytical errors in multi-step methods are predominantly additive, multiplicative, or a mixture of both.
    • To investigate the impact of 'blinding' quality-control samples on the additive and multiplicative error components.

    Main Methods:

    • Analysis of 'open' (analyst-identified) quality-control data from two hospitals for 11 different assays.

    Related Experiment Videos

  • Analysis of 'blind' (analyst-unidentified) quality-control data from one hospital for the same assays.
  • Characterization of overall error properties as additive, multiplicative, or mixed.

    • Main Results:

    • Overall analytical errors in current methodologies are typically mixed, indicating a combination of additive and multiplicative properties.
    • Predominantly additive and predominantly multiplicative overall errors were also observed, but less frequently than mixed errors.
    • Implementing a 'blinded' quality-control system tended to increase the multiplicative error component, while the additive component remained largely unaffected.

    Conclusions:

    • Multi-step analytical methods commonly exhibit mixed error properties, necessitating careful consideration beyond simple additive or multiplicative models.
    • Blinding QC samples can alter the error characteristics of assays, potentially by increasing the relative contribution of multiplicative errors.
    • These findings have implications for QC strategy design and the interpretation of assay performance in clinical laboratories.