Journal article
Gene-Environment Independence in Case-Control Studies: Issues of Parameterization and Bayesian Inference
Statistics in biosciences, v 7(2), pp 460-475
01 Oct 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We consider the problem of exploiting the gene-environment independence (GEI) assumption in a case-control study inferring the joint effect of genotype and environmental exposure on disease risk. Specifically, we focus on the special case that both genotype and environmental exposure are binary. We note that the prospective intercept can sometimes be identified as a pair of "twin" values. Also, the GEI and general maximum-likelihood estimators of the gene-environment interaction coincide if the data cell proportions are directly compatible with the GEI assumption. Further, we approach the problem in a Bayesian framework by reweighing the general posterior subject to the prior specified over the subset of parameter space that is consistent with the GEI assumption. Some simulation studies have been conducted to compare the proposed method to its general counterpart. Finally, we have also extended the proposed method to address the concern that the GEI assumption may sometimes be violated.
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Details
- Title
- Gene-Environment Independence in Case-Control Studies: Issues of Parameterization and Bayesian Inference
- Creators
- Hao Luo - University of British ColumbiaIgor Burstyn - Drexel UniversityPaul Gustafson - University of British Columbia
- Publication Details
- Statistics in biosciences, v 7(2), pp 460-475
- Publisher
- Springer Nature
- Number of pages
- 16
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Environmental and Occupational Health
- Web of Science ID
- WOS:000371507200016
- Scopus ID
- 2-s2.0-84943349394
- Other Identifier
- 991019169695604721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Mathematical & Computational Biology