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On binary longitudinal mixed models in adaptive clinical trials

机译:适应性临床试验中的二元纵向混合模型

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In an adaptive clinical trial research, it is common to use data dependent design weights to assign individuals to treatments so that more study subjects are assigned to a better treatment. These design weights must be exploited for the consistent estimation of the treatment effect. In an adaptive longitudinal clinical set-up, the repeated responses of an individual will, however, be affected by the design weights as well as individual random effects and certain fixed time effects. In this article, we provide an estimation approach that takes the variability of the individual random effects and the longitudinal correlations of the repeated responses into account, and produces consistent and efficient estimate for the treatment effect. The performance of this approach is examined through a simulation study.
机译:在适应性临床试验研究中,通常使用依赖数据的设计权重来将个体分配给治疗,以便将更多的研究对象分配给更好的治疗。必须使用这些设计权重来一致估计治疗效果。然而,在自适应纵向临床设置中,个体的重复响应将受到设计权重以及个体随机效应和某些固定时间效应的影响。在本文中,我们提供了一种估计方法,该方法将各个随机效应的变异性和重复响应的纵向相关性考虑在内,并对治疗效果产生一致且有效的估计。通过仿真研究检查了这种方法的性能。

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