Open AccessUnconditional analyses can increase efficiencyin assessing gene–environment interaction of the case-combined-control design
Author(s) -
Alisa M. Goldstein,
Marie-Gabrielle Dondon,
Nadine Andrieu
Publication year - 2006
Publication title -
international journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.406
H-Index - 208
eISSN - 1464-3685
pISSN - 0300-5771
DOI - 10.1093/ije/dyl048
Subject(s) - conditional logistic regression , interaction , main effect , statistics , conditional dependence , gene–environment interaction , statistical power , control (management) , logistic regression , computer science , odds ratio , mathematics , econometrics , gene , genetics , biology , artificial intelligence , genotype
A design combining both related and unrelated controls, named the case-combined-control design, was recently proposed to increase the power for detecting gene-environment (GxE) interaction. Under a conditional analytic approach, the case-combined-control design appeared to be more efficient and feasible than a classical case-control study for detecting interaction involving rare events.