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首页> 外文期刊>Journal of Multivariate Analysis: An International Journal >A parametric bootstrap approach for two-way ANOVA in presence of possible interactions with unequal variances
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A parametric bootstrap approach for two-way ANOVA in presence of possible interactions with unequal variances

机译:在存在方差不均等可能相互作用的情况下进行双向方差分析的参数自举方法

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摘要

In this article we consider the Two-Way ANOVA model with unequal cell frequencies without the assumption of equal error variances. For the problem of testing no interaction effects and equal main effects, we propose a parametric bootstrap (PB) approach and compare it with existing the generalized F (GF) test. The Type I error rates and powers of the tests are evaluated using Monte Carlo simulation. Our studies show that the PB test performs better than the generalized F-test. The PB test performs very satisfactorily even for small samples while the GF test exhibits poor Type I error properties when the number of factorial combinations or treatments goes up.
机译:在本文中,我们考虑具有不相等单元频率且没有相同误差方差假设的双向ANOVA模型。对于没有交互作用且主效应相等的测试问题,我们提出了一种参数自举(PB)方法,并将其与现有的广义F(GF)测试进行比较。使用蒙特卡洛模拟评估I型错误率和测试的功效。我们的研究表明,PB测试的性能要优于广义F检验。即使对于少量样品,PB测试也非常令人满意,而当阶乘组合或处理次数增加时,GF测试显示出较差的I型错误特性。

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