Abstract Details
Activity Number:
|
410
|
Type:
|
Topic Contributed
|
Date/Time:
|
Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Biometrics Section
|
Abstract - #308623 |
Title:
|
Combining Dependent P-Values Using Generalizations of Gamma Distribution with Applications to Multi-Trait Association
|
Author(s):
|
Gang Zheng*+ and Qizhai Li
|
Companies:
|
National Heart, Lung and Blood Institute and Academy of Mathematics and Systems Science, CAS
|
Keywords:
|
dependent tests ;
Fisher's combination ;
gamma distributions ;
pleiotrophic associations ;
genetic association ;
GWAS
|
Abstract:
|
Fisher's combination of p-values is a classical approach to combine independent test statistics. When the test statistics are dependent, the gamma distribution is most commonly used to fit the Fisher's combination test. We propose to use two generalizations of the gamma distribution for the Fisher's combination test. Our results show that both generalizations have better control type I error rates than the gamma distribution at more extreme tails. Applications of the results to genetic pleiotrophic associations are described, where multiple traits are tested for association with a marker.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.