Bayesian ROC curve estimation under verification bias
نویسندگان
چکیده
منابع مشابه
Bayesian ROC curve estimation under verification bias.
Receiver operating characteristic (ROC) curve has been widely used in medical science for its ability to measure the accuracy of diagnostic tests under the gold standard. However, in a complicated medical practice, a gold standard test can be invasive, expensive, and its result may not always be available for all the subjects under study. Thus, a gold standard test is implemented only when it i...
متن کاملBayesian ROC curve estimation under binormality using a rank likelihood
There are various methods to estimate the parameters in the binormal model for the ROC curve. In this paper, we propose a conceptually simple and computationally feasible Bayesian estimation method using a rank-based likelihood. Posterior consistency is also established. We compare the new method with other estimation methods and conclude that our estimator generally performs better than its co...
متن کاملBayesian bootstrap estimation of ROC curve.
Receiver operating characteristic (ROC) curve is widely applied in measuring discriminatory ability of diagnostic or prognostic tests. This makes the ROC analysis one of the most active research areas in medical statistics. Many parametric and semiparametric estimation methods have been proposed for estimating the ROC curve and its functionals. In this paper, we propose the Bayesian bootstrap (...
متن کاملSemiparametric estimation of the covariate-specific ROC curve in presence of ignorable verification bias.
Covariate-specific receiver operating characteristic (ROC) curves are often used to evaluate the classification accuracy of a medical diagnostic test or a biomarker, when the accuracy of the test is associated with certain covariates. In many large-scale screening tests, the gold standard is subject to missingness due to high cost or harmfulness to the patient. In this article, we propose a sem...
متن کاملBayesian ROC curve estimation under binormality using a partial likelihood based on ranks
There are various methods to estimate the parameters in the binormal model for the ROC curve. In this paper, we propose a conceptually simple and computationally accessible Bayesian estimation method using a partial likelihood based on ranks. Posterior consistency is also established. We compare the new method with other estimation methods and conclude that our estimator generally performs bett...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistics in Medicine
سال: 2014
ISSN: 0277-6715
DOI: 10.1002/sim.6297