Estimation of a Generalized Treatment Effect in a Control Group Versus Treatment Group Design

Abstract

A control group versus treatment group design is considered where the responses in the treatment group are modeled as a two-component mixture model that accounts for the possibility that only a fraction of the patients in the treated group will respond to the treatment. In this setting, the treatment effect is generalized to include both the fraction of treated patients that respond to the treatment and the magnitude of the response. Two alternative correlated and biased estimators are combined to yield an estimator that is preferable to either one of the estimators individually. The combined estimator is demonstrated on an illustrative blood pressure dataset.