Saumen Mandal

TL;DR: In this article, an optimal adaptive allocation for two treatments having some continuous responses was proposed for phase III clinical trials involving two binary responses having binary responses, but no covariate, where covariates were allowed in the model.

TL;DR: The idea is that, at an appropriate iterate p ( r ) , the single distribution should be replaced by conditional distributions within clusters and a marginal distribution across the clusters, which is formulated for a general regression model and then is explored through several regression models.

TL;DR: A class of multiplicative algorithms, indexed by a function f(.), which depends on the derivatives of the criterion function, is used to construct approximate optimizing distributions p j by maximizing a criterion function subject to the basic constraints on p"j of nonnegativity and summation to unity.

TL;DR: A class of multiplicative algorithms indexed by a function f (·) is used, shown to satisfy the basic constraints on the design weights of nonnegativity and summation to unity.

TL;DR: In this paper, a generalized framework is proposed to derive multi-treatment optimal response-adaptive designs for phase-III clinical trials, and a detailed performance study is provided for three treatment trials minimising failures.