主 题: Nonparametric estimation of the accuracy of diagnostic tests in the absence of the gold standard
报告人: Prof. Xiao-Hua Andrew Zhou (Department of Biostatistics, University of Washington)
时 间: 2006-07-05 上午 9:30 - 10:30
地 点: 理科一号楼 1418
In evaluation of diagnostic accuracy of tests, a gold standard on
the disease status is required. However, in many complex diseases,
it is impossible or unethical to obtain such the gold standard. If
an imperfect standard is used as if it were a gold standard, the
estimated accuracy of the tests would be biased. This type of bias
is called imperfect gold standard bias. In this talk we introduce a
maximum likelihood (ML) method for estimating ROC curves and their
areas of ordinal-scale tests in the absence a gold standard. Our
simulation study shows the proposed estimates for the ROC curve
areas have good finite-sample properties in terms of bias and mean
squared error (MSE). Finally we illustrate the application of the
proposed method in a real clinical study on assessing the accuracy
of seven specific pathologists in detecting carcinoma in situ of
the uterine cervix.
