The problem of allocating patients in a two treatment clinical trial with dichotomous response is considered. The trial goal is to determine the better treatment while incurring as few patient losses as possible. Several allocation rules are compared and it is found that bandit strategies perform well on both criteria in that they achieve nearly optimal power while keeping expected trial failures nearly minimal. The rules are also evaluated according to their computational complexity.
none3For clinical trials that compare two or more competing treatments, the literature proposes seve...
The paper assesses biased-coin designs for sequential treatment allocation in clinical trials. Compa...
We introduce a non-myopic, covariate-adjusted response adaptive (CARA) allocation design for multi-a...
Suppose two treatments with binary responses are available for patients with some disease and that e...
The problem of assigning one of several treatments in clinical trials is formulated as a discounted ...
Suppose two treatments with binary responses are available for patients with some disease. Sequentia...
In recent years, several authors have investigated allocation rules for comparative clinical trials,...
In experiments that consider the use of subjects, a crucial part is deciding which treatment to allo...
Key word and phrases. Decision theory, two-armed bandit problems, sequential treatment allocation, c...
Multi-armed bandit problems (MABPs) are a special type of optimal control problem that has been stud...
In recent years, several authors have investigated response-adaptive allocation rules for com-parati...
We propose a novel response‐adaptive randomization procedure for multi‐armed trials with continuous ...
Consider a Bayesian sequential allocation problem that incorporates a covariate. The goal is to maxi...
In experiments, researchers commonly allocate subjects randomly and equally to the different treatme...
We propose a novel response-adaptive randomization procedure for multi-armed trials with continuous ...
none3For clinical trials that compare two or more competing treatments, the literature proposes seve...
The paper assesses biased-coin designs for sequential treatment allocation in clinical trials. Compa...
We introduce a non-myopic, covariate-adjusted response adaptive (CARA) allocation design for multi-a...
Suppose two treatments with binary responses are available for patients with some disease and that e...
The problem of assigning one of several treatments in clinical trials is formulated as a discounted ...
Suppose two treatments with binary responses are available for patients with some disease. Sequentia...
In recent years, several authors have investigated allocation rules for comparative clinical trials,...
In experiments that consider the use of subjects, a crucial part is deciding which treatment to allo...
Key word and phrases. Decision theory, two-armed bandit problems, sequential treatment allocation, c...
Multi-armed bandit problems (MABPs) are a special type of optimal control problem that has been stud...
In recent years, several authors have investigated response-adaptive allocation rules for com-parati...
We propose a novel response‐adaptive randomization procedure for multi‐armed trials with continuous ...
Consider a Bayesian sequential allocation problem that incorporates a covariate. The goal is to maxi...
In experiments, researchers commonly allocate subjects randomly and equally to the different treatme...
We propose a novel response-adaptive randomization procedure for multi-armed trials with continuous ...
none3For clinical trials that compare two or more competing treatments, the literature proposes seve...
The paper assesses biased-coin designs for sequential treatment allocation in clinical trials. Compa...
We introduce a non-myopic, covariate-adjusted response adaptive (CARA) allocation design for multi-a...