Assessing accuracy of a continuous screening test in the presence of verification bias

• Published in: Applied statistics Vol. 54; no. 1; pp. 173 - 190
• Main Authors: Alonzo, Todd A., Pepe, Margaret Sullivan
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.01.2005; Blackwell Publishers; Blackwell; Royal Statistical Society; Oxford University Press
• Series: Journal of the Royal Statistical Society Series C
• Subjects: Accuracy; Applications; Area under the curve; Bias; Combinatorics; Combinatorics. Ordered structures; Consistent estimators; Designs and configurations; Disease models; Disease prevalence rates; Distribution theory; Estimate reliability; Estimation bias; Estimators; Exact sciences and technology; Experimental design; Hearing loss; Imputation; Infants; Inverse probability weighting; Mathematics; Mean score; Medical diagnosis; Medical research; Neonatal hearing screening; Probability and statistics; Probability theory and stochastic processes; Receiver operating characteristic curve; Research methodology; Sampling bias; Sciences and techniques of general use; Screening tests; Semiparametric estimators; Sensitivity; Specificity; Statistical analysis; Statistics; Studies; Bias; Estimator robustness; Statistical simulation; Screening test; Relative efficiency; Statistics; Experimental design; Misspecification model; Distribution function; Receiver operating characteristic curves; Binary response; Application; Biased estimation
• ISSN: 0035-9254; 1467-9876
• DOI: 10.1111/j.1467-9876.2005.00477.x

In studies to assess the accuracy of a screening test, often definitive disease assessment is too invasive or expensive to be ascertained on all the study subjects. Although it may be more ethical or cost effective to ascertain the true disease status with a higher rate in study subjects where the screening test or additional information is suggestive of disease, estimates of accuracy can be biased in a study with such a design. This bias is known as verification bias. Verification bias correction methods that accommodate screening tests with binary or ordinal responses have been developed; however, no verification bias correction methods exist for tests with continuous results. We propose and compare imputation and reweighting bias-corrected estimators of true and false positive rates, receiver operating characteristic curves and area under the receiver operating characteristic curve for continuous tests. Distribution theory and simulation studies are used to compare the proposed estimators with respect to bias, relative efficiency and robustness to model misspecification. The bias correction estimators proposed are applied to data from a study of screening tests for neonatal hearing loss.