Permutation tests for linear models
Permutation tests for linear models
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DOI：
10.1111/1467-842x.00156
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发表时间：
2001-03-01
影响因子：
1.1
通讯作者：
Robinson, J
中科院分区：
文献类型：
--
作者：
Anderson, MJ;Robinson, J
基于样本偏相关，线性模型中的偏回归系数的检验已经提出了几种近似排列检验。本文首先对一个精确检验进行了解释和说明。然后比较了所提出的各种排列方法下检验统计量的分布，表明排列下的偏相关性渐近联合正态，均值为0，方差为1。Freedman & Lane（1983）的方法与精确检验的相关系数为1，其他方法与精确检验的相关系数较小。在局部替代下，所有近似置换检验的临界值都收敛于同一个常数，因此它们都具有相同的渐近功效。仿真验证了这些理论结果。
Several approximate permutation tests have been proposed for tests of partial regression coefficients in a linear model based on sample partial correlations. This paper begins with an explanation and notation for an exact test. It then compares the distributions of the test statistics under the various permutation methods proposed, and shows that the partial correlations under permutation are asymptotically jointly normal with means 0 and variances 1. The method of Freedman & Lane (1983) is found to have asymptotic correlation 1 with the exact test, and the other methods are found to have smaller correlations with this test. Under local alternatives the critical values of all the approximate permutation tests converge to the same constant, so they all have the same asymptotic power. Simulations demonstrate these theoretical results.