DeepAI AI Chat
Log In Sign Up

Nonparametric MANOVA in Mann-Whitney effects

12/19/2017
by   Dennis Dobler, et al.
0

Multivariate analysis of variance (MANOVA) is a powerful and versatile method to infer and quantify main and interaction effects in metric multivariate multi-factor data. It is, however, neither robust against change in units nor a meaningful tool for ordinal data. Thus, we propose a novel nonparametric MANOVA. Contrary to existing rank-based procedures we infer hypotheses formulated in terms of meaningful Mann-Whitney-type effects in lieu of distribution functions. The tests are based on a quadratic form in multivariate rank effect estimators and critical values are obtained by the bootstrap. This newly developed procedure consequently provides asymptotically exact and consistent inference for general models such as the nonparametric Behrens-Fisher problem as well as multivariate one-, two-, and higher-way crossed layouts. Computer simulations in small samples confirm the reliability of the developed method for ordinal as well as metric data with covariance heterogeneity. Finally, an analysis of a real data example illustrates the applicability and correct interpretation of the results.

READ FULL TEXT

page 1

page 2

page 3

page 4

02/04/2021

Incompletely observed nonparametric factorial designs with repeated measurements: A wild bootstrap approach

In many life science experiments or medical studies, subjects are repeat...
10/12/2017

Wild Bootstrapping Rank-Based Procedures: Multiple Testing in Nonparametric Split-Plot Designs

Split-plot or repeated measures designs are frequently used for planning...
03/01/2018

Nonparametric Analysis of Clustered Multivariate Data

There has been a wide interest to extend univariate and multivariate non...
04/12/2019

New statistic for detecting laboratory effects in ORDANOVA

The present study defines a new statistic for detecting laboratory effec...
01/27/2023

Inference for all variants of the multivariate coefficient of variation in factorial designs

The multivariate coefficient of variation (MCV) is an attractive and eas...