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The Practical Significance of Measurement Error in Pulmonary Function Testing Conducted in Research Settings

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  • Richard B. Belzer
  • R. Jeffrey Lewis

Abstract

Conventional spirometry produces measurement error by using repeatability criteria (RC) to discard acceptable data and terminating tests early when RC are met. These practices also implicitly assume that there is no variation across maneuvers within each test. This has implications for air pollution regulations that rely on pulmonary function tests to determine adverse effects or set standards. We perform a Monte Carlo simulation of 20,902 tests of forced expiratory volume in 1 second (FEV1), each with eight maneuvers, for an individual with empirically obtained, plausibly normal pulmonary function. Default coefficients of variation for inter‐ and intratest variability (3% and 6%, respectively) are employed. Measurement error is defined as the difference between results from the conventional protocol and an unconstrained, eight‐maneuver alternative. In the default model, average measurement error is shown to be ∼5%. The minimum difference necessary for statistical significance at p

Suggested Citation

  • Richard B. Belzer & R. Jeffrey Lewis, 2019. "The Practical Significance of Measurement Error in Pulmonary Function Testing Conducted in Research Settings," Risk Analysis, John Wiley & Sons, vol. 39(10), pages 2316-2328, October.
    • Handle: RePEc:wly:riskan:v:39:y:2019:i:10:p:2316-2328
    DOI: 10.1111/risa.13315
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