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Log-rank permutation tests for trend: Saddlepoint p-values and survival rate confidence intervals

机译:对数趋势的对数秩检验:鞍点p值和生存率置信区间

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Suppose p + 1 experimental groups correspond to increasing dose levels of a treatment and all groups are subject to right censoring. In such instances, permutation tests for trend can be performed based on statistics derived from the weighted log-rank class. This article uses saddlepoint methods to determine the mid-P-values for such permutation tests for any test statistic in the weighted log-rank class. Permutation simulations are replaced by analytical saddlepoint computations which provide extremely accurate mid-P-values that are exact for most practical purposes and almost always more accurate than normal approximations. The speed of mid-P-value computation allows for the inversion of such tests to determine confidence intervals for the percentage increase in mean (or median) survival time per unit increase in dosage.
机译:假设p + 1个实验组对应于增加的治疗剂量水平,并且所有组均应接受正确的检查。在这种情况下,可以基于从加权对数等级得出的统计数据执行趋势的排列检验。本文使用鞍点方法为加权对数等级中的任何测试统计量确定此类置换测试的中P值。置换模拟被解析鞍点计算所取代,该鞍点计算提供了极其精确的中P值,该值对于大多数实际目的都是精确的,并且几乎总是比法线逼近更准确。中P值计算的速度允许对此类测试进行反演,以确定单位剂量增加的平均(或中位)生存时间增加百分比的置信区间。

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