José Antonio Moler Cuiral , Fernando Plo , Miguel San Miguel Marco
An adaptive design for a clinical trial with prognostic factors and more than two treatments is described using a generalised urn model in a random environment. Patients arrive sequentially and treatments are applied according to a function of the urn composition. This function may change at each stage. Patient's response is immediate and discrete, with a finite number of possible values. The evolution of the urn composition is expressed by a recurrence equation that fits the Robbins-Monro scheme of stochastic approximation. In this setting, we obtain asymptotic properties for the performance of each treatment and we illustrate the application of the rule with an example.
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