A PAIRED PRENTICE-WILCOXON TEST FOR CENSORED PAIRED DATA
A PAIRED PRENTICE-WILCOXON TEST FOR CENSORED PAIRED DATA
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DOI：
10.2307/2531957
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发表时间：
1987-03-01
期刊：
影响因子：
1.9
通讯作者：
FLEMING, TR
中科院分区：
文献类型：
--
作者：
OBRIEN, PC;FLEMING, TR
普伦蒂斯（1978，Biometrika 65，167-179）提供了经典线性秩统计的删失数据推广。本文研究了将普伦蒂斯统计量推广到截尾配对数据分析中的一种方法。特别强调的是配对数据版本的普伦蒂斯-威尔科克森统计，讨论的原因，更喜欢普伦蒂斯的Gehan分数。配对Prentice-Wilcoxon（PPW）统计量利用了块间信息，可以被视为Conover-Iman（1981，The American Statistician 35，124-129）“秩对配对t检验”或Lam-Longnecker（1983，Biometrika 70，510-513）修改的Wilcoxon秩和统计量的删失数据概括。在比较PPW、符号和广义符号秩（GSR）统计量的模拟中，PPW对除指数尺度之外的所有替代方案都是最强大的。此外，如果引入离群值对，则GSR相对于PPW在该替代方案中的小优势丧失。当与双样本Prentice-Wilcoxon统计量相比时，PPW在不相关数据中几乎同样强大，并且随着成对成员之间的相关性增加，其功效变得上级。
Prentice (1978, Biometrika 65, 167-179) has provided a censored-data generalization of classical linear rank statistics. This paper investigates a method to generalize the Prentice statistics to the analysis of censored paired data. Particular emphasis is given to the paired-data version of the Prentice-Wilcoxon statistic, with discussion of the reasons for preferring Prentice over the Gehan scores. The paired Prentice-Wilcoxon (PPW) statistic makes use of interblock information and can be viewed as a censored-data generalization of the Conover-Iman (1981, The American Statistician 35, 124-129) "paired t test on the ranks" or of the Lam-Longnecker (1983, Biometrika 70, 510-513) modified Wilcoxon rank sum statistic. In simulations comparing the PPW, sign, and generalized signed rank (GSR) statistics, the PPW is most powerful against all but the exponential scale alternative. Furthermore, the small advantage of the GSR over the PPW in that alternative is lost if outlier pairs are introduced. When compared to the two-sample Prentice-Wilcoxon statistic, the PPW is nearly as powerful in uncorrelated data and its power becomes superior as correlation between paired members increases.