|
Activity Number:
|
406
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Thursday, August 15, 2002 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
General Methodology
|
| Abstract - #300649 |
|
Title:
|
Group Testing with Small-Sized Pools
|
|
Author(s):
|
Joshua Tebbs*+ and Barry Moser+
|
|
Affiliation(s):
|
Oklahoma State University and Duke University
|
|
Address:
|
301C MSCS, Stillwater, Oklahoma, 74078, USA Duke University School of Medicine, Durham, North Carolina, 27710, USA
|
|
Keywords:
|
Group testing ; Empirical Bayes estimation ; Pooling designs ; Composite sampling ; Hepatitis C virus ; HIV seroprevalence
|
|
Abstract:
|
Group testing has long been recognized as a safe and sensible alternative to one-at-a-time testing in applications where the prevalence rate is small. However, oftentimes the group size is smaller than statistically optimal, because one lacks prior knowledge about the true prevalence or the testing procedures used to make group observations suffer from low sensitivity or specificity. In light of this, we propose an empirical Bayes (EB) procedure to estimate the true prevalence. The EB estimator is shown to be preferred over the usual maximum likelihood estimator (MLE), when the prevalence rate and group size are both small. Within the EB framework, we discuss interval estimation, the use of various loss functions, and approaches on combining data from multiple studies. The proposed methods are illustrated using group-testing data from a prospective hepatitis C virus study conducted in Xuzhou City, China.
|
- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
Back to the full JSM 2002 program |
