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Activity Number: 159
Type: Topic Contributed
Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #312687 View Presentation
Title: Joint Analysis of Binary and Quantitative Traits with Data Sharing and Outcome-Dependent Sampling
Author(s): Jungnam Joo*+
Companies: National Cancer Center, Korea
Keywords: case-control ; continuous trait ; F-test ; polygenetic pleiotropy ; scaled chi-square distribution ; trend test
Abstract:

We study the analysis of a joint association between a genetic marker with both binary and quantitative traits, where the quantitative trait values are only available for the cases due to data sharing and outcome-dependent sampling. Data sharing becomes common in genetic association studies, and the outcome-dependent sampling is the consequence of data sharing, under which a phenotype of interest is not measured for some subgroup. The trend test and F -test are often, respectively, used to analyze the binary and quantitative traits. Because of the outcome-dependent sampling, the usual F -test can be applied using the subgroup with the observed quantitative traits. We propose a modified F -test by also incorporating the genotype frequencies of the subgroup whose traits are not observed. Further, a combination of this modified F -test and Pearson's test is proposed by Fisher's combination of their P-values as a joint analysis. Because of the correlation of the two analyses, we propose to use a Gamma (scaled chi-squared) distribution to fit the asymptotic null distribution for the joint analysis. The proposed modified F -test and the joint analysis can also be applied to test single t


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