Abstract
When mean treatment difference is not considered valid to quantify treatment effect for endpoints measured in continuous or ordinal scales in clinical trials because small treatment gains may not be clinically relevant, data on individuals are often dichotomized into responder versus non-responder. Thus, differences in responder rates between treatments are used to quantify the treatment effect, without incorporating the sizes of treatment gains in responders. Sizes of treatment gains provide information on how good the treatment is in responders, while the sizes in non-responders are clinically irrelevant. It is therefore important to incorporate information on treatment gains in responders when assessing the treatment difference. In this article, we propose a new way of quantifying the treatment effect, referred to as weighted responder mean, by making complete use of the information available in responders. Tests for treatment differences using weighted responder means are proposed. Examples of using this weighted responder mean analysis are illustrated.