Quantile Regression in the Secondary Analysis of Case-Control Data.
Ontology highlight
ABSTRACT: Case-control design is widely used in epidemiology and other fields to identify factors associated with a disease. Data collected from existing case-control studies can also provide a cost-effective way to investigate the association of risk factors with secondary outcomes. When the secondary outcome is a continuous random variable, most of the existing methods focus on the statistical inference on the mean of the secondary outcome. In this paper, we propose a quantile-based approach to facilitating a comprehensive investigation of covariates' effects on multiple quantiles of the secondary outcome. We construct a new family of estimating equations combining observed and pseudo outcomes, which lead to consistent estimation of conditional quantiles using case-control data. Simulations are co
SUBMITTER: Wei Y
PROVIDER: S-EPMC6347118 | biostudies-literature | 2016
REPOSITORIES: biostudies-literature
ACCESS DATA