Davis C S
Department of Preventive Medicine, University of Iowa, Iowa City 52242.
Stat Med. 1991 Oct;10(10):1555-63. doi: 10.1002/sim.4780101007.
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.
在检验双向列联表中行变量和列变量的独立性时，标准的皮尔逊卡方统计量和似然比卡方统计量通常功效较低，尤其是随着表格维度的增加。本文描述了基于具有名义行分类和列分类的表格关联模型的似然比和得分统计量的单自由度独立性检验。得分统计量特别易于使用，因为它可以以封闭形式表示，计算简单，并且其大小和功效属性仅略逊于更复杂的似然比统计量。
