Assessment of Diagnostic Technologies: Methodology for Unbiased Estimation from Samples of Selectively Verified Patients


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Abstract

Concern with the efficacy of diagnostic technologies has stimulated numerous studies aimed at quantifying the discriminatory properties of various tests and procedures. These have focused principally on estimations of the result conditional probabilities, given disease status, eg, the sensitivity and specificity or the ROC curve. A source of bias in estimating these probabilities that is often unavoidable is created by the existence of a nonrandom selection mechanism for determining which patients initially tested will receive definitive verification of disease status. Correction for verification bias requires frequency data on the test results and any symptoms or other factors that influence selection for verification, both in the verified sample and in the source sample of patients tested.

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