Tests for homogeneity of the risk difference when data are sparse.
Tests for homogeneity of the risk difference when data are sparse.
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DOI：
10.2307/2534003
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发表时间：
1998-03
期刊：
影响因子：
1.9
通讯作者：
S. Lipsitz;K. Dear;N. Laird;G. Molenberghs
中科院分区：
文献类型：
--
作者：
S. Lipsitz;K. Dear;N. Laird;G. Molenberghs
提出了数据稀疏时一系列 2 x 2 表的风险差异同质性检验统计。加权最小二乘统计通常用于测试表中风险差异的相等性；然而，当数据稀疏时，该统计数据可能会出现反保守的 I 类错误率。模拟用于将建议的检验统计量与加权最小二乘统计量进行比较。加权最小二乘统计量在所有比较的统计量中具有最反保守的 I 类错误率。我们建议使用我们提出的检验统计量之一，而不是加权最小二乘统计量。
Test statistics for the homogeneity of the risk difference for a series of 2 x 2 tables when the data are sparse is proposed. A weighted least squares statistic is commonly used to test for equality of the risk difference over the tables; however, when the data are sparse, this statistic can have anticonservative Type I error rates. Simulation is used to compare the proposed test statistics to the weighted least squares statistic. The weighted least squares statistic has the most anticonservative Type I error rates of all the statistics compared. We suggest the use of one of our proposed test statistics instead of the weighted least squares statistic.