EVALUATION OF APPROXIMATED AND EXACT MULTIVARIATE TESTS FOR MEAN VECTORS: A DATA SIMULATION STUDY
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...
| Autores: | , , , , , , |
|---|---|
| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2022 |
| País: | Brasil |
| Recursos: | Universidade Federal de Lavras (UFLA) |
| Repositório: | Brazilian Journal of Biometrics |
| Idioma: | inglês |
| OAI Identifier: | oai:biometria.ufla.br:article/560 |
| Acesso em linha: | https://biometria.ufla.br/index.php/BBJ/article/view/560 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Likelihood ratio test Hotelling's T2 type I error most powerful test |
| Resumo: | 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. |
|---|