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Comparison of exact tests for association in unordered contingency tables using standard, mid-p, and randomized test versions

机译:使用标准,中期和随机测试版本比较无序列联表中关联的精确测试

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Pearson's chi-square (Pe), likelihood ratio (LR), and Fisher (Fi)-Freeman-Halton test statistics are commonly used to test the association of an unordered r x c contingency table. Asymptotically, these test statistics follow a chi-square distribution. For small sample cases, the asymptotic chi-square approximations are unreliable. Therefore, the exact p-value is frequently computed conditional on the row- and column-sums. One drawback of the exact p-value is that it is conservative. Different adjustments have been suggested, such as Lancaster's mid-p version and randomized tests. In this paper, we have considered 3 x 2, 2 x 3, and 3 x 3 tables and compared the exact power and significance level of these test's standard, mid-p, and randomized versions. The mid-p and randomized test versions have approximately the same power and higher power than that of the standard test versions. The mid-p type-Ⅰ error probability seldom exceeds the nominal level. For a given set of parameters, the power of Pe, LR, and Fi differs approximately the same way for standard, mid-p, and randomized test versions. Although there is no general ranking of these tests, in some situations, especially when averaged over the parameter space, Pe and Fi have the same power and slightly higher power than LR. When the sample sizes (i.e., the row sums) are equal, the differences are small, otherwise the observed differences can be 10% or more. In some cases, perhaps characterized by poorly balanced designs, LR has the highest power.
机译:皮尔逊卡方(Pe),似然比(LR)和Fisher(Fi)-Freeman-Halton测试统计数据通常用于测试无序r x c列联表的关联。渐近地,这些检验统计量遵循卡方分布。对于小样本情况,渐近卡方近似是不可靠的。因此,精确的p值通常以行和列和为条件进行计算。精确的p值的缺点之一是它很保守。提出了不同的调整方法,例如兰开斯特的中p版本和随机测试。在本文中,我们考虑了3 x 2、2 x 3和3 x 3的表格,并比较了这些测试的标准版本,中间版本和随机版本的确切功效和显着性水平。中级和随机测试版本的功率与标准测试版本的功率大致相同,并且功率更高。中p型Ⅰ型错误概率很少超过标称水平。对于给定的一组参数,Pe,LR和Fi的功效对于标准,中-p和随机测试版本几乎相同。尽管没有对这些测试进行一般排名,但是在某些情况下,尤其是在参数空间上进行平均时,Pe和Fi具有相同的功效,并且比LR略高。当样本大小(即行总和)相等时,差异很小,否则观察到的差异可以是10%或更大。在某些情况下,也许以平衡设计不佳为特征,LR的功率最高。

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