Generalized Confidence Interval Estimation for the Difference in Paired Areas Under the ROC Curves in the Absence of a Gold Standard
| Autor: | Feng-chen Chang, Shean-Ya Yeh, Hsin-neng Hsieh |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Statistics and Probability
Disease status Receiver operating characteristic Heuristic (computer science) media_common.quotation_subject Gold standard (test) Confidence interval Modeling and Simulation Expectation–maximization algorithm Statistics Area under the roc curve Normality Mathematics media_common |
| Zdroj: | Communications in Statistics - Simulation and Computation. 42:2056-2072 |
| ISSN: | 1532-4141 0361-0918 |
| DOI: | 10.1080/03610918.2012.690483 |
| Popis: | Receiver operating characteristic (ROC) curves can be used to assess the accuracy of tests measured on ordinal or continuous scales. The most commonly used measure for the overall diagnostic accuracy of diagnostic tests is the area under the ROC curve (AUC). A gold standard (GS) test on the true disease status is required to estimate the AUC. However, a GS test may be too expensive or infeasible. In many medical researches, the true disease status of the subjects may remain unknown. Under the normality assumption on test results from each disease group of subjects, we propose a heuristic method of estimating confidence intervals for the difference in paired AUCs of two diagnostic tests in the absence of a GS reference. This heuristic method is a three-stage method by combining the expectation-maximization (EM) algorithm, bootstrap method, and an estimation based on asymptotic generalized pivotal quantities (GPQs) to construct generalized confidence intervals for the difference in paired AUCs in the absenc... |
| Databáze: | OpenAIRE |
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