Multivariate nonparametric methods in two-way balanced designs: performances and limitations in small samples.

ABSTRACT: Investigations of multivariate population are pretty common in applied researches, and the two-way crossed factorial design is a common design used at the exploratory phase in industrial applications. When assumptions such as multivariate normality and covariance homogeneity are violated, the conventional wisdom is to resort to nonparametric tests for hypotheses testing. In this paper we compare the performances, and in particular the power, of some nonparametric and semi-parametric methods that have been developed in recent years. Specifically, we examined resampling methods and robust versions of classical multivariate analysis of variance (MANOVA) tests. In a simulation study, we generate data sets with different configurations of factor's effect, number of replicates, number of respons

SUBMITTER: Ronchi F 

PROVIDER: S-EPMC9041798 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature