Department of Statistics and Operations Research, 16767Universitat Politècnica de Catalunya, Barcelona, Spain.
Center for Medical Statistics, Informatics and Intelligent Systems, 27271Medical University of Vienna, Vienna, Austria.
Stat Methods Med Res. 2022 Feb;31(2):225-239. doi: 10.1177/09622802211048030. Epub 2021 Dec 6.
We propose a class of two-sample statistics for testing the equality of proportions and the equality of survival functions. We build our proposal on a weighted combination of a score test for the difference in proportions and a weighted Kaplan-Meier statistic-based test for the difference of survival functions. The proposed statistics are fully non-parametric and do not rely on the proportional hazards assumption for the survival outcome. We present the asymptotic distribution of these statistics, propose a variance estimator, and show their asymptotic properties under fixed and local alternatives. We discuss different choices of weights including those that control the relative relevance of each outcome and emphasize the type of difference to be detected in the survival outcome. We evaluate the performance of these statistics with small sample sizes through a simulation study and illustrate their use with a randomized phase III cancer vaccine trial. We have implemented the proposed statistics in the R package SurvBin, available on GitHub (https://github.com/MartaBofillRoig/SurvBin).
我们提出了一类用于检验比例相等和生存函数相等的两样本统计量。我们的建议基于比例差异的得分检验和基于加权 Kaplan-Meier 统计量的生存函数差异检验的加权组合。所提出的统计量是完全非参数的，不依赖于生存结果的比例风险假设。我们给出了这些统计量的渐近分布，提出了一个方差估计量，并在固定和局部替代假设下展示了它们的渐近性质。我们讨论了不同的权重选择，包括那些控制每个结果的相对相关性的权重，并强调了在生存结果中要检测的差异类型。我们通过模拟研究评估了这些统计量在小样本量下的性能，并通过随机化 III 期癌症疫苗试验说明了它们的用法。我们已经在 R 包 SurvBin 中实现了所提出的统计量，该包可在 GitHub 上获得（https://github.com/MartaBofillRoig/SurvBin）。
