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Comparison of Several Means under Heterogeneity: Over-mean-rank Function Approach

机译:异质性下几种方法的比较:均值秩函数法

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In practice it is often of interest to compare the medians or means of several populations that are not assumed to have equal variances. A method is proposed that depends on the over-mean-rank function that is defined as the percentage of the ranks over the global mean rank in each group. Chi-square distribution is found to give a very good fit for this function. The main advantages for the proposed method are: stable in terms of Type I error; less affected by ties and can be shown graphically. Comparison with Kruskal-Wallis, Welch and ANOVA methods are given for unbalanced designs and not equal variances from normal and non-normal populations in terms of Type I error. The simulation results are shown that the proposed method improves the Type I error and its performance exhibits superior robustness over the studied methods.
机译:在实践中,通常比较比较假定不具有相等方差的多个总体的中位数或均值。提出了一种方法,该方法依赖于均值秩函数,该函数定义为每组中秩在全局平均秩上的百分比。发现卡方分布非常适合此功能。所提出的方法的主要优点是:在I类错误方面稳定;受领带的影响较小,并且可以通过图形显示。对于非平衡设计,给出了与Kruskal-Wallis,Welch和ANOVA方法的比较,并且就I型误差而言,正常人群和非正常人群的方差均不相等。仿真结果表明,所提出的方法改善了I类误差,并且其性能比所研究的方法具有更好的鲁棒性。

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