Tutorial on Biostatistics: Receiver-Operating Characteristic (ROC) Analysis for Correlated Eye Data.

ABSTRACT:

Purpose

To demonstrate methods for receiver-operating characteristic (ROC) analysis of correlated eye data.

Methods

We applied the Obuchowski's nonparametric approach and cluster bootstrap for estimating and comparing the area under ROC curve (AUC) between different sets of predictors to three datasets with varying inter-eye correlation.

Results

In an optic neuritis (ON) study of 152 eyes (80 patients), the AUC of optical coherence tomography retinal nerve fiber layer thickness for diagnosing ON (inter-eye kappa = 0.13) was 0.71 [95% confidence interval (95% CI): 0.622, 0.792] from the naïve approach without accounting for inter-eye correlation was narrower than from nonparametric (95% CI: 0.613, 0.801) or cluster bootstrap (95% CI: 0.614, 0.797) approaches. In an ana

SUBMITTER: Ying GS 

PROVIDER: S-EPMC8586066 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature