Modeling Multiple Responses via Bootstrapping Margins with an Application to Genetic Association Testing.

ABSTRACT: The need for analysis of multiple responses arises from many applications. In behavioral science, for example, comorbidity is a common phenomenon where multiple disorders occur in the same person. The advantage of jointly analyzing multiple correlated responses has been examined and documented. Due to the difficulties of modeling multiple responses, nonparametric tests such as generalized Kendall's Tau have been developed to assess the association between multiple responses and risk factors. These procedures have been applied to genomewide association studies of multiple complex traits. Unfortunately, those nonparametric tests only provide the significance of the association but not the magnitude. We propose a Gaussian copula model with discrete margins for modeling multivariate binary res

SUBMITTER: Zhao J 

PROVIDER: S-EPMC4629876 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature