Summarizing Monte Carlo results in methodological research: The single-factor, fixed-effects ANCOVA case
Summarizing Monte Carlo results in methodological research: The single-factor, fixed-effects ANCOVA case
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DOI：
10.3102/10769986028001045
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发表时间：
2003-03-01
影响因子：
2.4
通讯作者：
Harwell, M
中科院分区：
文献类型：
--
作者：
Harwell, M
精确统计理论和蒙特卡罗研究的结果提供了证据，证明协方差分析中F检验的检验大小和功率对某些假设的违反很敏感。然而，尚未对违反假设的影响作出全面总结。本文采用元分析方法，对单因素、协方差模型的固定效应分析中F检验的检验大小和检验幂的蒙特卡罗研究结果进行了总结，更新和扩展了本文文献的叙述性综述。对协方差模型分析中非参数秩变换检验的蒙特卡罗结果进行了分析。提出了在违反假设时使用这些测试的准则，以促进更明智地使用这些程序。
Results from exact statistical theory and Monte Carlo studies have provided evidence that the test size and power of the F test in analysis of covariance are sensitive to violations of certain assumptions. However, a comprehensive summary of the effect of assumption violations has not been available. In this article, meta-analytic methods are used to summarize the results of Monte Carlo studies of the test size and power of the F test in the single-factor, fixed-effects analysis of covariance model, updating and extending narrative reviews of this literature. Monte Carlo results for the nonparametric rank-transform test in the analysis of covariance model are also analyzed. Guidelines for using these tests when assumptions are violated are presented to promote more judicious use of these procedures.