The Nonparametric Combination (NPC) is a flexible permutation-based methodology that can be adopted to deal with a wide range of complex problems, including the comparison of two or more populations when a multivariate outcome is observed. We propose on a new NPC-based testing procedure to address a specific multivariate problem in which C 2 paired samples and multiple data types are available. A simulation study is proposed to evaluate the performances of our proposal under several challenging scenarios. A real-data application is also considered. Data were gathered through a questionnaire that was submitted to multiple respondents, asking them to evaluate a product in terms of a certain set of KPIs after multiple time frames. A number of experiments were also conducted and several continuous KPIs were measured after the same time frames. The NPC-based test was therefore adopted to compare the performances of the product across time.

A multivariate permutation test for the analysis of C-paired samples in the presence of multiple data types

Rosa Arboretti;Elena Barzizza;Riccardo Ceccato;Luigi Salmaso
2022

Abstract

The Nonparametric Combination (NPC) is a flexible permutation-based methodology that can be adopted to deal with a wide range of complex problems, including the comparison of two or more populations when a multivariate outcome is observed. We propose on a new NPC-based testing procedure to address a specific multivariate problem in which C 2 paired samples and multiple data types are available. A simulation study is proposed to evaluate the performances of our proposal under several challenging scenarios. A real-data application is also considered. Data were gathered through a questionnaire that was submitted to multiple respondents, asking them to evaluate a product in terms of a certain set of KPIs after multiple time frames. A number of experiments were also conducted and several continuous KPIs were measured after the same time frames. The NPC-based test was therefore adopted to compare the performances of the product across time.
2022
Book of Abstracts
Computational and Methodological Statistics (CMStatistics 2022)
978-9925-7812-6-3
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3492526
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