scholarly journals On testing the equality of mean vectors in high dimension

Author(s):  
Muni S. Srivastava
1991 ◽  
Vol 16 (2) ◽  
pp. 125-139 ◽  
Author(s):  
James Algina ◽  
Takako C. Oshima ◽  
K. Linda Tang

Type I error rates for Yao’s, James’ first order, James’ second order, and Johansen’s tests of equality of mean vectors for two independent samples were estimated for various conditions defined by the degree of heteroscedasticity and nonnormality (uniform, Laplace, t(5), beta (5, 1.5), exponential, and lognormal distributions). For these alternatives to Hotelling’s T2, variance-covariance homogeneity is not an assumption. Although the four procedures can be seriously nonrobust with exponential and lognormal distributions, they were fairly robust with the rest of the distributions. The performance of Yao’s test, James’ second order test, and Johansen’s test was slightly superior to the performance of James’ first order test.


2010 ◽  
Vol 39 (3) ◽  
pp. 487-500 ◽  
Author(s):  
Nobumichi Shutoh ◽  
Makiko Kusumi ◽  
Wataru Morinaga ◽  
Shunichi Yamada ◽  
Takashi Seo

1988 ◽  
Vol 13 (3) ◽  
pp. 281-290 ◽  
Author(s):  
James Algina ◽  
Kezhen L. Tang

For Yao’s and James’ tests, Type I error rates were estimated for various combinations of the number of variables (p), samplesize ratio (n1: n2), sample-size-to-variables ratio, and degree of heteroscedasticity. These tests are alternatives to Hotelling’s T2 and are intended for use when the variance-covariance matrices are not equal in a study using two independent samples. The performance of Yao’s test was superior to that of James’. Yao’s test had appropriate Type I error rates when p ≥ 10, (n1 + n2)/p ≥ 10, and 1:2 ≤ n1:n2 ≤ 2:1. When (n1 + n2)/p = 20, Yao’s test was robust when n1: n2 was 5:1, 3:1, and 4:1 and p was 2, 6, and 10, respectively.


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