A General Multi-Treatment Adaptive Design for Multivariate Responses

Abstract

ABSTRACT A general adaptive allocation design is proposed for continuous multivariate responses where the covariance matrix of the response vectors is unknown. There are K > 2 competing treatments, possible prognostic factors are considered in the allocation procedure, potential delayed responses are allowed for, and treatment-covariate interactions are incorporated. The allocation rule for any incoming patient is dependent on all the allocation-and-response-and-prognostic factor history of the previously allocated patients as well as the prognostic factor vector of the current patient. The design is a generalization of the approach suggested by Bandyopadhyay and Biswas (2001), which was presented for a much simpler scenario. The performance characteristics of the proposed design and some follow-up inference procedures are studied analytically and also numerically illustrated. An extension of the present approach to the situation where some components of the response vectors are continuous and some binary is then considered. Some further extensions of the work are briefly indicated. Recommended by Nitis Mukhopadhyay