In Adaptive Designs, N. Flournoy and W.F. Rosenberger, eds.,
IMS Lecture Notes--Monograph Series
25, 1995, pp. 65-87.
A Modified Bandit as an Approach to Ethical Allocation
in Clinical Trials
Janis Hardwick
Statistics Department, University of Michigan
Abstract:
A sequential allocation rule based on an optimal strategy for a two-armed
bandit problem is proposed for use in the problem of identifying the better
of two treatment alternatives in clinical trials. The purpose of the rule
is to ensure more ethical alloction of patients while retaining a given
probability of correctly selecting the better treatment at the end of the
trial. The behavior of the bandit rule is compared with two other
commonly proposed allocation rules: play-the-winner and vector-at-a-time.
It is found that, in general, the bandit rule performs as well as, and usually
better than, both of the other allocation rules. All comparisons are
based on exact computations using forward induction algorithms carried
out on desktop workstations.
Keywords: ethics, clinical trials, adaptive designs, bandit allocation,
bayesian, frequentist, correct selection, indifference regions, expected
successes lost
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Last modified: 3 Mar 1997 |