Abstract

For the sequential parallel comparison design with normally distributed outcomes and re-randomization at the start of phase 2, we propose fitting separate repeated measures models for the two phases. We show analytically the asymptotic independence between the treatment effect estimators in the two phases. We recommend pre-specification of the weights for combining the treatment effects in the two phases and use of the t reference distribution with the Welch-Satterthwaite degrees of freedom for testing the overall treatment effect when the sample size is small. We use simulation studies to demonstrate that the proposed method controls type I error and has proper coverage of 95% confidence intervals.

摘要

对于阶段2开始时具有正态分布结果和重新随机化的顺序并行比较设计，我们建议为两个阶段拟合单独的重复测量模型。我们分析地显示了两个阶段中治疗效果估计量之间的渐近独立性。我们建议预先确定权重，以结合两个阶段的治疗效果，并在样本量较小时使用t参考分布和Welch-Satterthwaite自由度来测试总体治疗效果。我们使用仿真研究来证明所提出的方法可控制I型错误，并能正确覆盖95％的置信区间。