|
Activity Number:
|
65
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Sunday, July 29, 2007 : 4:00 PM to 5:50 PM
|
|
Sponsor:
|
Biopharmaceutical Section
|
| Abstract - #309745 |
|
Title:
|
Estimation of Diagnostic Accuracy Measures for a Binocular Test
|
|
Author(s):
|
Daniel Bonzo*+ and Alexander R. de Leon
|
|
Companies:
|
Altus Pharmaceuticals, Inc. and University of Calgary
|
|
Address:
|
125 Sidney Street, Cambridge, MA, 02703,
|
|
Keywords:
|
Common correlation model ; correlated binary data ; coverage probability ; predictive values ; sensitivity ; specificity
|
|
Abstract:
|
Diagnostic studies in ophthalmology frequently involve binocular data where pairs of eyes are evaluated, through some diagnostic procedure, for the presence of certain diseases or pathologies. The simplest approach of estimating measures of diagnostic accuracy, such as sensitivity and specificity, treats eyes as independent. Approaches which account for the inter-eye correlation include regression methods using GEE and likelihood techniques based on various correlated binomial models. The paper proposes a simple alternative methodology of estimating measures of diagnostic accuracy for binocular tests based on a flexible model for correlated binary data. Moments estimation of model parameters is outlined and asymptotic inference is discussed. The computation of the estimators and their standard errors are illustrated with data from a study on diabetic retinopathy.
|
