Format

Send to:

Choose Destination
See comment in PubMed Commons below
J Stat Plan Inference. 2009 Mar 1;139(1):711-721.

Bounding Sample Size Projections for the Area Under a ROC Curve.

Author information

  • 1Center for Statistical Sciences, Brown University, Providence RI 02912, Email at jblume@stat.brown.edu.

Abstract

Studies of diagnostic tests are often designed with the goal of estimating the area under the receiver operating characteristic curve (AUC) because the AUC is a natural summary of a test's overall diagnostic ability. However, sample size projections dealing with AUCs are very sensitive to assumptions about the variance of the empirical AUC estimator, which dependens on two correlation parameters. While these correlation parameters can be estimated from available data, in practice it is hard to find reliable estimates before the study is conducted. Here we derive achievable bounds on the projected sample size that are free of these two correlation parameters. The lower bound is the smallest sample size that would yield the desired level of precision for some model, while the upper bound is the smallest sample size that would yield the desired level of precision for all models. These bounds are important reference points when designing a single or multi-arm study; they are the absolute minimum and maximum sample size that would ever be required. When the study design includes multiple readers or interpreters of the test, we derive bounds pertaining to the average reader AUC and the 'pooled' or overall AUC for the population of readers. These upper bounds for multireader studies are not too conservative when several readers are involved.

PMID:
20160839
[PubMed]
PMCID:
PMC2631183
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for PubMed Central
    Loading ...
    Write to the Help Desk