Information-regret compromise in covariate-adaptive treatment allocation
Information-regret compromise in covariate-adaptive treatment allocation
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DOI：
10.1214/16-aos1518
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发表时间：
2017-10
影响因子：
4.5
通讯作者：
A. Metelkina;L. Pronzato
中科院分区：
文献类型：
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作者：
A. Metelkina;L. Pronzato
当必须在信息（关于每种治疗的成功概率对有影响力的协变量的依赖性）和成本（就接受最差治疗的受试者数量而言）之间做出妥协时，考虑协变量适应性治疗分配。信息通过设计准则进行参数估计，成本是可加的，与成功概率有关。在近似设计理论的框架内，最优配置的确定形成了一个复合设计问题。我们表明，当协变量是i.i.d.对于概率测度μ，其解与以μ为界的最优设计测度的构造具有很强的相似性。我们通过等价定理来描述最优设计，并构造了一个协变量自适应的顺序分配策略，该策略收敛于最优。我们的新的最优设计可以作为其他更常见的分配方法的基准。一个响应自适应的实现是可能的实际应用与未知的模型参数。提供了几个说明性的例子。
Covariate-adaptive treatment allocation is considered in the situation when a compromise must be made between information (about the dependency of the probability of success of each treatment upon influential covariates) and cost (in terms of number of subjects receiving the poorest treatment). Information is measured through a design criterion for parameter estimation, the cost is additive and is related to the success probabilities. Within the framework of approximate design theory, the determination of optimal allocations forms a compound design problem. We show that when the covariates are i.i.d. with a probability measure µ, its solution possesses strong similarities with the construction of optimal design measures bounded by µ. We characterize optimal designs through an Equivalence Theorem and construct a covariate-adaptive sequential allocation strategy that converges to the optimum. Our new optimal designs can be used as benchmarks for other, more usual, allocation methods. A response-adaptive implementation is possible for practical applications with unknown model parameters. Several illustrative examples are provided.