Group Sequential Methods for ROC Curves

Comparative diagnostic studies in which each patient has two tests conducted or has several diseased and nondiseased observations for each test will generate correlated or clustered ROC curves. The traditional ROC comparison methods applied on the correlated or clustered data can result in incorrect statistical inference. Furthermore, to design and apply group sequential method in these comparative trials, we need to derive the theoretical variance-covariance structure and the joint distribution of sequential statistics. We first derive the theoretical covariance structure of sequential correlated and clustered ROCs' difference and further verify the findings through simulation studies. Then based on the independent increments covariance structure that we have proved, we conduct group sequential studies for comparing ROC curves on both simulated and real data.

Author

• Ye, Xuan

• Statistics
• Clustered
• Correlated
• Group Sequential Method
• NPV
• PPV
• ROC

Identifier

hdl:1920/10446

OAI identifier oai:identifier

oai:MARS:1920/10446