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Designing one-sided group sequential clinical trials to detect a mixture alternative

机译：设计单方面的团体顺序临床试验以检测替代药物

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We consider the construction of one-sided group sequential designs where the stopping rule includes boundaries for early stopping to accept for futility and to reject for efficacy. The traditional assumption that all patients have the same likelihood of benefiting from the treatment is sometimes unrealistic and can underestimate the required sample size. This motivates us to power the design for an alternative where the treatment group observations come from a mixture of normal distributions. For the proposed setting, we use standardized test statistics based on sample means, and the test turns out to be an L-optimal similar test. Stopping boundaries and arm size for the design are determined by Type I and Type II error spending equations. We demonstrate the need for larger arm sizes when trying to detect a mixture alternative compared to trying to detect a pure shift alternative. The unknown variance case is discussed. With the mixture model, we discuss a more general definition of treatment effect. The maximum likelihood estimator for the treatment effect is discussed.
机译：我们考虑了一种单面小组顺序设计的构造，其中停止规则包括提前停止的边界，以接受徒劳和拒绝效力。传统假设所有患者都具有从治疗中获益的可能性相同，这有时是不现实的，并且可能低估了所需的样本量。这激励我们为设计提供动力，使治疗组的观察结果来自正态分布的混合。对于建议的设置，我们使用基于样本均值的标准化测试统计数据，该测试结果证明是L最优的相似测试。设计的止动边界和臂尺寸由I型和II型误差消耗方程式确定。我们证明，相比于单纯的变速选择，在尝试检测混合动力选择时需要更大的手臂尺寸。讨论了未知方差情况。通过混合模型，我们讨论了治疗效果的更一般定义。讨论了治疗效果的最大似然估计。

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