This paper deals with the problem of allocating patients to two competing treatments in the presence of covariates in order to achieve a good trade-off between efficiency, ethical concern and randomization. We propose a compound criterion that combines inferential precision and ethical gain by flexible weights depending on the unknown treatment effects. In the absence of treatment-covariate interactions, this criterion leads to a locally optimal allocation which does not depend on the covariates and can be targeted by a suitable implementation of the doubly-adaptive biased coin design aimed at balancing the roles of randomization, ethics and information. Some properties of the suggested procedure are described.
CITATION STYLE
Jones, B. (2010). mODa 9 – Advances in Model-Oriented Design and Analysis, (October 2010), 0–15. Retrieved from http://link.springer.com/10.1007/978-3-7908-2410-0
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