Novel likelihood ratio tests for screening gene-gene and gene-environment interactions with unbalanced repeated-measures data.

ABSTRACT: There has been extensive literature on modeling gene-gene interaction (GGI) and gene-environment interaction (GEI) in case-control studies with limited literature on statistical methods for GGI and GEI in longitudinal cohort studies. We borrow ideas from the classical two-way analysis of variance literature to address the issue of robust modeling of interactions in repeated-measures studies. While classical interaction models proposed by Tukey and Mandel have interaction structures as a function of main effects, a newer class of models, additive main effects and multiplicative interaction (AMMI) models, do not have similar restrictive assumptions on the interaction structure. AMMI entails a singular value decomposition of the cell residual matrix after fitting the additive main effects and

SUBMITTER: Ko YA 

PROVIDER: S-EPMC4009698 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature