Applications of the Wei-Lachin multivariate one-sided test for multiple outcomes on possibly different scales.
Applications of the Wei-Lachin multivariate one-sided test for multiple outcomes on possibly different scales.
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DOI：
10.1371/journal.pone.0108784
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Lachin JM
中科院分区：
文献类型：
--
作者：
Lachin JM
许多研究的目的是评估与对照组相比，一种治疗方法是否同时对多种结果有利。通常，对一组结果没有差异的联合零假设使用对多个测试进行校正的单独测试进行测试，或者使用多变量T2类Manova或全局测试进行测试。然而，在这种情况下，更有效的测试是多变量单边或单向测试，旨在检测对每个结果的同时有益的治疗效果，尽管不一定具有相同的幅度。魏-拉钦检验是一种简单的1df检验，从最初在多变量秩次分析中描述的成分统计的简单和中获得。在温和的条件下，这项测试提供了对治疗组之间对于所有结果没有差异的零假设与替代假设的最大有效检验，该替代假设认为实验治疗对部分或全部组成部分的结果比对照更好，并且对于任何一个都不会更差。在此，描述了对所有潜在不同规模的手段、比例或寿命及其组合的多个差异的同时测试的应用。还描述了这种分析的样本量和功率的评估。对于单位方差和相关系数均为0.025.5的两个结果的均值的检验，在0.0 5水平上为两个单独的单侧检验提供90%威力所需的样本量比在0.0 5水平上的单一魏-拉钦多变量单向检验所需的样本量大%。因此，具有这些操作特性的魏-拉钦测试比两个单独的测试效率高39%。同样，与2df上的T2类综合检验相比，魏-拉钦检验的效率提高了32%。给出了多组分的魏-拉钦检验优于复合结果检验的一个例子。
Many studies aim to assess whether a therapy has a beneficial effect on multiple outcomes simultaneously relative to a control. Often the joint null hypothesis of no difference for the set of outcomes is tested using separate tests with a correction for multiple tests, or using a multivariate T 2-like MANOVA or global test. However, a more powerful test in this case is a multivariate one-sided or one-directional test directed at detecting a simultaneous beneficial treatment effect on each outcome, though not necessarily of the same magnitude. The Wei-Lachin test is a simple 1 df test obtained from a simple sum of the component statistics that was originally described in the context of a multivariate rank analysis. Under mild conditions this test provides a maximin efficient test of the null hypothesis of no difference between treatment groups for all outcomes versus the alternative hypothesis that the experimental treatment is better than control for some or all of the component outcomes, and not worse for any. Herein applications are described to a simultaneous test for multiple differences in means, proportions or life-times, and combinations thereof, all on potentially different scales. The evaluation of sample size and power for such analyses is also described. For a test of means of two outcomes with a common unit variance and correlation 0.5, the sample size needed to provide 90% power for two separate one-sided tests at the 0.025 level is 64% greater than that needed for the single Wei-Lachin multivariate one-directional test at the 0.05 level. Thus, a Wei-Lachin test with these operating characteristics is 39% more efficient than two separate tests. Likewise, compared to a T 2-like omnibus test on 2 df, the Wei-Lachin test is 32% more efficient. An example is provided in which the Wei-Lachin test of multiple components has superior power to a test of a composite outcome.
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影响因子：
158.5
作者：
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通讯作者：
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通讯作者：
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作者：
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