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000132495 037__ $$aDKFZ-2018-00182
000132495 041__ $$aeng
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000132495 1001_ $$aLiu, Gang$$b0
000132495 245__ $$aRobust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence.
000132495 260__ $$aOxford$$bOxford Univ. Press$$c2018
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000132495 520__ $$aThere have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium.
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000132495 7001_ $$aMukherjee, Bhramar$$b1
000132495 7001_ $$aLee, Seunggeun$$b2
000132495 7001_ $$aLee, Alice W$$b3
000132495 7001_ $$aWu, Anna H$$b4
000132495 7001_ $$aBandera, Elisa V$$b5
000132495 7001_ $$aJensen, Allan$$b6
000132495 7001_ $$aRossing, Mary Anne$$b7
000132495 7001_ $$aMoysich, Kirsten B$$b8
000132495 7001_ $$0P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253$$aChang-Claude, Jenny$$b9$$udkfz
000132495 7001_ $$aDoherty, Jennifer A$$b10
000132495 7001_ $$aGentry-Maharaj, Aleksandra$$b11
000132495 7001_ $$aKiemeney, Lambertus$$b12
000132495 7001_ $$aGayther, Simon A$$b13
000132495 7001_ $$aModugno, Francesmary$$b14
000132495 7001_ $$aMassuger, Leon$$b15
000132495 7001_ $$aGoode, Ellen L$$b16
000132495 7001_ $$aFridley, Brooke L$$b17
000132495 7001_ $$aTerry, Kathryn L$$b18
000132495 7001_ $$aCramer, Daniel W$$b19
000132495 7001_ $$aRamus, Susan J$$b20
000132495 7001_ $$aAnton-Culver, Hoda$$b21
000132495 7001_ $$aZiogas, Argyrios$$b22
000132495 7001_ $$aTyrer, Jonathan P$$b23
000132495 7001_ $$aSchildkraut, Joellen M$$b24
000132495 7001_ $$aKjaer, Susanne K$$b25
000132495 7001_ $$aWebb, Penelope M$$b26
000132495 7001_ $$aNess, Roberta B$$b27
000132495 7001_ $$aMenon, Usha$$b28
000132495 7001_ $$aBerchuck, Andrew$$b29
000132495 7001_ $$aPharoah, Paul D$$b30
000132495 7001_ $$aRisch, Harvey$$b31
000132495 7001_ $$aPearce, Celeste Leigh$$b32
000132495 7001_ $$aConsortium, Ovarian Cancer Association$$b33$$eCollaboration Author
000132495 773__ $$0PERI:(DE-600)2030043-8$$a10.1093/aje/kwx243$$gVol. 187, no. 2, p. 366 - 377$$n2$$p366 - 377$$tAmerican journal of epidemiology$$v187$$x1476-6256$$y2018
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