Exact Inferences on Paired ROC Curves
Date Issued
2007
Date
2007
Author(s)
Li, Chi-Rong
DOI
en-US
Abstract
The receiver operating characteristic (ROC) curve is currently a popular statistical tool for the accuracy of diagnostic device. It has been widely used in various practical applications, such as radiology, psychiatry, epidemiology, biomedical informatics, etc. One of the primary objectives of diagnostic trials is to compare the diagnostic accuracy of the new diagnostic device to that of the current standard device. The area under the ROC curve (AUROC) is a summary index that is interpreted as the average of true positive rate over entire false positive rates. The partial area under the ROC curve (PAUROC) is another summary index that restricts attention to a specified range of clinical interest. They can be usually used as the bases of inferential statistics for comparing ROC curves. In this dissertation, we develop exact inferences for comparing paired AUROCs and paired PAUROCs based on the concept of generalized p-values and generalized confidence intervals. In addition, we extend the results to compare the paired ROC curves which are constructed by multiple markers. Simulation results demonstrate that the exact test based on generalized p-values adequately controls the size at the nominal level; the exact interval estimation based on the generalized confidence intervals provides not only sufficient coverage probability but also reasonable expected length. In general, the proposed methods outperform some published asymptotic maximum likelihood methods and nonparametric methods in various simulation scenarios. Furthermore, numerical examples using published datasets illustrate the proposed methods.
Subjects
廣義檢定變數, 廣義樞紐量, 廣義p值, 廣義信賴區間, 多重標記
generalized test variable, generalized pivotal quantity, generalized p-value, generalized confidence interval, multiple markers
Type
thesis
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