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Retrospective likelihood‐based methods for analyzing case‐cohort genetic association studies
Author(s) -
Shen Yuanyuan,
Cai Tianxi,
Chen Yu,
Yang Ying,
Chen Jinbo
Publication year - 2015
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12342
Subject(s) - association (psychology) , retrospective cohort study , computer science , statistics , genetic association , cohort , medicine , computational biology , econometrics , mathematics , genetics , biology , genotype , psychology , gene , single nucleotide polymorphism , psychotherapist
Summary The case cohort (CCH) design is a cost‐effective design for assessing genetic susceptibility with time‐to‐event data especially when the event rate is low. In this work, we propose a powerful pseudo‐score test for assessing the association between a single nucleotide polymorphism (SNP) and the event time under the CCH design. The pseudo‐score is derived from a pseudo‐likelihood which is an estimated retrospective likelihood that treats the SNP genotype as the dependent variable and time‐to‐event outcome and other covariates as independent variables. It exploits the fact that the genetic variable is often distributed independent of covariates or only related to a low‐dimensional subset. Estimates of hazard ratio parameters for association can be obtained by maximizing the pseudo‐likelihood. A unique advantage of our method is that it allows the censoring distribution to depend on covariates that are only measured for the CCH sample while not requiring the knowledge of follow‐up or covariate information on subjects not selected into the CCH sample. In addition to these flexibilities, the proposed method has high relative efficiency compared with commonly used alternative approaches. We study large sample properties of this method and assess its finite sample performance using both simulated and real data examples.