Regularized outcome weighted subgroup identification for differential treatment effects.

ABSTRACT: To facilitate comparative treatment selection when there is substantial heterogeneity of treatment effectiveness, it is important to identify subgroups that exhibit differential treatment effects. Existing approaches model outcomes directly and then define subgroups according to interactions between treatment and covariates. Because outcomes are affected by both the covariate-treatment interactions and covariate main effects, direct modeling outcomes can be hard due to model misspecification, especially in presence of many covariates. Alternatively one can directly work with differential treatment effect estimation. We propose such a method that approximates a target function whose value directly reflects correct treatment assignment for patients. The function uses patient outcomes as weig

SUBMITTER: Xu Y 

PROVIDER: S-EPMC5395466 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature