Asymptotics in response-adaptive designs generated by a two-color, randomly reinforced urn

TL;DR

This paper studies the asymptotic properties of a response-adaptive clinical trial design using a two-color, randomly reinforced urn model, demonstrating optimal treatment assignment and estimator normality.

Contribution

It provides a novel approach to establish joint asymptotic normality of estimators despite extreme allocation proportions in a reinforced urn model.

Findings

Establishes asymptotic normality of treatment response estimators.

Analyzes the rate of convergence of patient allocation.

Studies the asymptotic behavior of test statistics.

Abstract

This paper illustrates asymptotic properties for a response-adaptive design generated by a two-color, randomly reinforced urn model. The design considered is optimal in the sense that it assigns patients to the best treatment, with probability converging to one. An approach to show the joint asymptotic normality of the estimators of the mean responses to the treatments is provided in spite of the fact that allocation proportions converge to zero and one. Results on the rate of convergence of the number of patients assigned to each treatment are also obtained. Finally, we study the asymptotic behavior of a suitable test statistic.