EVALUATION OF APPROXIMATED AND EXACT MULTIVARIATE TESTS FOR MEAN VECTORS: A DATA SIMULATION STUDY
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Abstract
The present study aimed to evaluate, through data simulation, the multivariate statistical tests Likelihood ratio test (LRT) and Hotelling’s T2 test for mean vectors regarding the type I error rate and the power of test. The scenarios were designed to analyze test performance under the influence of p−variate normality, correlation, and homogeneity of variance, as well as number of variables and sample size. Our results show that the type I error rate was not affected by the violation of the assumptions of independence and homogeneity of variances, due to the presence of p−variate normality, differently from the power of test. In data simulation of p−variate distribution with heavier tails than usual (Student−t with 1 degree of freedom), the Hotelling’s T2 showed to be conservative, while the LRT showed better results, especially for small sample sizes.
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