On the LBI criterion for the multivariate one-way random effects model under non-normality

被引:0
|
作者
Harrar, SW
Gupta, AK [1 ]
机构
[1] Bowling Green State Univ, Dept Math & Stat, Bowling Green, OH 43403 USA
[2] S Dakota State Univ, Dept Math & Stat, Brookings, SD 57007 USA
关键词
random effects model; variance components; LBI test; asymptotic expansions; multivariate analysis of variance; robustness; non-normality;
D O I
10.1080/02331880500186185
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The asymptotic null distribution of the locally best invariant (LBI) test criterion for testing the random effect in the one-way multivariable analysis of variance model is derived under normality and non-normality. The error of the approximation is characterized as O(1/n). The non-null asymptotic distribution is also discussed. In addition to providing a way of obtaining percentage points and p-values, the results of this paper are useful in assessing the robustness of the LBI criterion. Numerical results are presented to illustrate the accuracy of the approximation.
引用
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页码:405 / 414
页数:10
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