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Quantile Regression in the Secondary Analysis of Case-Control Data.


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 conducted to evaluate the performance of our proposed approach, and a case-control study on genetic association with asthma is used to demonstrate the method.

SUBMITTER: Wei Y 

PROVIDER: S-EPMC6347118 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Quantile Regression in the Secondary Analysis of Case-Control Data.

Wei Ying Y   Song Xiaoyu X   Liu Mengling M   Ionita-Laza Iuliana I   Reibman Joan J  

Journal of the American Statistical Association 20160505 513


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 facilita  ...[more]

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