Implementing multiple imputations for addressing missing data in multireader multicase design studies.

ABSTRACT:

Background

In computer-aided diagnosis (CAD) studies utilizing multireader multicase (MRMC) designs, missing data might occur when there are instances of misinterpretation or oversight by the reader or problems with measurement techniques. Improper handling of these missing data can lead to bias. However, little research has been conducted on addressing the missing data issue within the MRMC framework.

Methods

We introduced a novel approach that integrates multiple imputation with MRMC analysis (MI-MRMC). An elaborate simulation study was conducted to compare the efficacy of our proposed approach with that of the traditional complete case analysis strategy within the MRMC design. Furthermore, we applied these approaches to a real MRMC design CAD study on aneurysm detection v

SUBMITTER: Pan Z 

PROVIDER: S-EPMC11428558 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature