A Bayesian adaptive design in clinical trials for continuous responses

Adaptive design is a popular concept in several clinical trials, especially in phase III trials. The idea is to allocate treatments to the entering patients according to the state of art of the present data, i.e., to allocate a larger number of patients to the better treatment. The present paper provides a Bayesian formulation of an adaptive allocation design for clinical trials that considers all the continuous responses along with the associated covariates for future allocation. Some Bayesian inferences followed by the allocation are discussed along with a Bayesian prediction for future allocation. The convergence of the allocation probabilities is also discussed along with some related logistics of the design.