A one degree of freedom nominal association model for testing independence in two-way contingency tables.
A one degree of freedom nominal association model for testing independence in two-way contingency tables.
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一种单自由度名义关联模型，用于测试双向列联表中的独立性。
DOI：
10.1002/sim.4780101007
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发表时间：
1991
影响因子：
2
通讯作者：
Davis,CS
中科院分区：
文献类型：
--
作者：
Davis,CS
在检验双向列联表中行变量和列变量的独立性时，标准皮尔逊和似然比卡方统计量通常具有较低的功效，特别是当表的维度增加时。本文描述了基于似然比和分数统计的一自由度独立性检验，该检验来自具有名义行和列分类的表的关联模型。分数统计特别容易使用，因为它可以用封闭的形式表示，易于计算，并且具有大小和功率特性，仅略低于更复杂的似然比统计。
In testing the independence of the row and column variables in a two‐way contingency table, the standard Pearson and likelihood ratio chi‐square statistics often have low power, especially as the dimensions of the table increase. In this paper, one degree of freedom tests of independence based on likelihood ratio and score statistics from an association model for tables with nominal row and column classifications are described. The score statistic is especially easy to use, since it can be expressed in closed form, is simple to compute, and has size and power properties which are only slightly inferior to those of the more complicated likelihood ratio statistic.