Recursive Combination Tests
递归组合检验AI 解读 ↓
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递归组合检验
- 研究问题
- 如何允许试验根据已有信息调整后续设计、中期分析次数和决策边界，同时控制总体检验的第一类错误率？
- 方法与思路
- 作者递归应用两阶段 p 值组合检验，将下一阶段的 p 值替换为后续组合检验的 p 值，并串联组合函数得到总体 p 值。
- 材料陈述的贡献
- 摘要称程序在一般条件下控制检验水平，涵盖经典组序贯与两阶段自适应检验，并便于计算置信区间和中位无偏估计。
- 阅读关注点
- 核对组合 p 值函数的有效性条件、阶段间信息与适应规则，以及区间和点估计如何从最终检验程序构造。
- 阅读边界
- 仅据稿件版本未注明的 OpenAlex 摘要；所谓一般条件未展开，不能认为任意数据依赖调整均有效，也未提供功效比较结果。
原文摘要
We present a method that extends the flexibility of adaptive designs to the number of interim analyses and to the choice of decision boundaries. At each stage of the trial, the design of the next stage can be determined using all of the information gathered so far. Additionally, one can specify the next stage as the final stage or can plan a further interim analysis. The method is based on a recursive application of the two-stage combination tests for p values. The crucial point is the appropriate definition of a p value function that combines p values from two separate stages to a single p value. Formally, we start with a two-stage combination test. However, the p value of the second stage can be replaced by the p value of a further combination test. This applies if the experimenter decides in the first interim analysis to perform another interim analysis, thereby extending the design to at least three stages. Obviously, this can be also done in a recursive way in the following interim analyses. The test decision is based on an overall p value, which can be easily calculated by concatenation of the p value functions for the combination tests used. Under very general conditions, this procedure controls the level α. Recursive combination tests cover the classical group sequential and adaptive two-stage tests as special cases. By construction, they also allow for simple computation of confidence intervals and median unbiased point estimates.