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数据稀疏时风险差异的齐性检验。

Tests for homogeneity of the risk difference when data are sparse.

作者信息

Lipsitz S R, Dear K B, Laird N M, Molenberghs G

机构信息

Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.

出版信息

Biometrics. 1998 Mar;54(1):148-60.

PMID:9544513
Abstract

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.

摘要

针对数据稀疏时一系列2×2表格风险差异的齐性,提出了检验统计量。加权最小二乘统计量通常用于检验各表格间风险差异的相等性;然而,当数据稀疏时,该统计量可能具有反保守的I型错误率。通过模拟将所提出的检验统计量与加权最小二乘统计量进行比较。在所有比较的统计量中,加权最小二乘统计量具有最反保守的I型错误率。我们建议使用我们提出的检验统计量之一,而非加权最小二乘统计量。

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