论文标题
一类二进制和事件时间结果的两样本非参数统计
A class of two-sample nonparametric statistics for binary and time-to-event outcomes
论文作者
论文摘要
我们提出了一类两样本统计数据，用于测试比例平等和生存功能的平等。我们建立了针对比例差异和加权Kaplan-Meier统计统计测试的得分测试的加权组合的建议。所提出的统计数据是完全非参数，并且不依赖于生存结果的比例危害假设。我们介绍了这些统计数据的渐近分布，提出了一个方差估计器，并在固定和局部替代方案下显示其渐近特性。我们讨论了权重的不同选择，包括控制每个结果的相对相关性的权重，并强调生存结果中要检测到的差异类型。我们通过模拟研究评估了这些统计数据的性能，并说明了它们通过随机III期癌症疫苗试验的使用。我们已经在github（https://github.com/martabofilloig/survbin）上获得的R软件包Survbin中实施了拟议的统计信息。
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 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).
