This paper provides a fixed-width confidence interval of a real-valued functional, which involves the comparison between the univariate distribution functions, under a response-adaptive design in which a Stein-type two-stage procedure is carried out.

U BANDYOPADHYAY

A BISWAS

University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

&nbsp;

The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

&nbsp;

It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

Statistics and Probability Letters

This article provides a two-stage procedure to develop a fixed-width confidence interval of log odds ratio in a joint binomial and inverse binomial setting where the stopping rule is obtained by adopting a two-stage procedure on the number of index subjects for the inverse sampling. A purely sequential version of this procedure is also studied. Different asymptotic results associated with the procedures are obtained. The findings are supported by detailed simulation study followed by one data example. © 2017 Taylor & Francis.

Sequential Analysis

Fixed-width confidence interval of log odds ratio for joint binomial and inverse binomial sampling

The use of ridit, as a probability score, is a very common practice to compare discrete random variables in discrete data analysis. In the present work we formulate ridit reliability functionals for some comparison of K independent binary random variables. We use such functionals to provide a generalized response-adaptive design (GRAD) on K(≥+2) treatment-arms for dichotomous response variables. We exhibit some properties of the proposed design and compare it with some of the existing competitors by computing its various performance measures. We also provide a discussion towards a possible modification of the GRAD in the presence of covariates. © 2011 Copyright Taylor and Francis Group, LLC.

Communications in Statistics - Theory and Methods

On multi-treatment adaptive allocation design for dichotomous response

A randomized two-stage adaptive design is proposed and studied for allocation of patients to treatments and comparison in a phase III clinical trial with survival time as treatment responses. We consider the possibility of several covariates in the design and analysis. Several exact and limiting properties of the design and the follow-up inference are studied, both numerically and theoretically. The applicability of the proposed methodology is illustrated by using some real data. © 2010 The Authors. Journal compilation © 2010 VVS.

Statistica Neerlandica

A covariate-adjusted adaptive design for two-stage clinical trials with survival data

In the present work we use ridit, a measure comparing two discrete random variables, to develop a two-treatment response adaptive allocation technique in the presence of a stochastic prognostic factor. Various exact and asymptotic performance measures of the proposed technique are obtained and are compared with that of the existing techniques. © 2008 The Korean Statistical Society.

Journal of the Korean Statistical Society

Two-treatment covariate-dependent response adaptive allocation design for dichotomous response

A randomized two-stage adaptive Bayesian design is proposed and studied for allocation and comparison in a phase III clinical trial with survival time as treatment response. Several exact and limiting properties of the design and the follow-up inference are studied, both numerically and theoretically, and are compared with a single-stage randomized procedure. The applicability of the proposed methodology is illustrated by using some real data. © Springer Science+Business Media, LLC 2009.

Journal	Data powered by TypesetStatistics and Probability Letters
Publisher	Data powered by TypesetElsevier
ISSN	0167-7152