Verification Bias
Impact and Methods for Correction when Assessing Accuracy of Diagnostic Tests
DOI:
https://doi.org/10.57805/revstat.v12i1.144Keywords:
imputation, inverse probability weighting, ROC curve, sensitivity, specificityAbstract
Sometimes it is not feasible to obtain disease status verification for all study subjects. Analysis of only those with disease ascertainment can result in biased estimates of the accuracy (sensitivity, specificity, ROC curve) of a diagnostic test, screening test, or biomarker if the estimation method does not properly account for the missing disease ascertainment. This paper discusses the impact of this bias, verification bias, when estimating the accuracy of dichotomous and continuous diagnostic tests. In addition, methods to correct for verification bias are described. Areas that require additional attention are also highlighted.
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Copyright (c) 2014 REVSTAT-Statistical Journal
This work is licensed under a Creative Commons Attribution 4.0 International License.