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Testing treatment‐by‐period interaction in four‐period crossover trials

机译:在四周期交叉试验中测试逐期相互作用

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Statistical analyses of crossover clinical trials have mainly focused on assessing the treatment effect, carryover effect, and period effect. When?a treatment‐by‐period interaction is plausible, it is important to test such interaction first before making inferences on differences among individual treatments. Considerably less attention has been paid to the treatment‐by‐period interaction, which has historically been aliased with the carryover effect in two‐period or three‐period designs. In this article, from the data of a newly developed four‐period crossover design, we propose a statistical method to compare the effects of two active drugs with respect to two response variables. We study estimation and hypothesis testing considering the treatment‐by‐period interaction. Constrained least squares is used to estimate the treatment effect, period effect, and treatment‐by‐period interaction. For hypothesis testing, we extend a general multivariate method for analyzing the crossover design with multiple responses. Results from simulation studies have shown that this method performs very well. We also illustrate how to apply our method to the real data problem.
机译:交叉临床试验的统计分析主要集中在评估治疗效果、结转效应和周期效应。什么时候分期治疗的相互作用是合理的,在推断个体治疗之间的差异之前,首先测试这种相互作用是很重要的。对分期治疗相互作用的关注程度要低得多,历史上,在两期或三期设计中,这种相互作用与结转效应混在一起。在本文中,根据新开发的四周期交叉设计的数据,我们提出了一种统计方法来比较两种活性药物对两个反应变量的影响。我们研究估计和假设检验,考虑到治疗周期的相互作用。约束最小二乘法用于估计治疗效果、周期效应和逐周期治疗相互作用。对于假设检验,我们扩展了一种通用的多变量方法来分析具有多个响应的交叉设计。仿真研究结果表明,该方法性能良好。我们还说明了如何将我们的方法应用于实际数据问题。

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