Result: The Multivariate Randomized Complete Block Design: A Novel Permutation Solution in Case of Ordered Categorical Variables : Statistics for Complex Problems: Permutation Testing Methos and Related Topics
Title:
The Multivariate Randomized Complete Block Design: A Novel Permutation Solution in Case of Ordered Categorical Variables : Statistics for Complex Problems: Permutation Testing Methos and Related Topics
Source:
Communications in statistics. Theory and methods. 41(16-18):3094-3109
Publisher Information:
Philadelphia, PA: Taylor & Francis, 2012.
Publication Year:
2012
Physical Description:
print, 1/2 p
Original Material:
INIST-CNRS
Subject Terms:
Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Généralités, General topics, Lois de probabilités, Distribution theory, Plans d'expériences, Experimental design, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Probabilités et statistiques numériques, Numerical methods in probability and statistics, Analyse multivariable, Multivariate analysis, Análisis multivariable, Analyse numérique, Numerical analysis, Análisis numérico, Distribution statistique, Statistical distribution, Distribución estadística, Estimation erreur, Error estimation, Estimación error, Estimation non paramétrique, Non parametric estimation, Estimación no paramétrica, Etude cas, Case study, Estudio caso, Loi n variables, Multivariate distribution, Ley n variables, Méthode Monte Carlo, Monte Carlo method, Método Monte Carlo, Méthode statistique, Statistical method, Método estadístico, Méthode stochastique, Stochastic method, Método estocástico, Permutation, Permutación, Plan bloc, Block design, Plan bloque, Plan expérience, Experimental design, Plan experiencia, Plan randomisé, Randomized design, Plan aleatorizado, Queue distribution, Distribution tail, Cola distribución, Queue lourde, Heavy tail, Cola pesada, Simulation statistique, Statistical simulation, Simulación estadística, Statistique test, Test statistic, Estadística test, Test comparaison, Comparison test, Test comparación, Test statistique, Statistical test, Test estadístico, Théorie approximation, Approximation theory, 62E17, 62K10, 65C05, Test permutation, Permutation test, Multivariate Randomized Complete Block designs, Ordered categorical responses, Permutation tests, Primary 62G09, Secondary 62G10, Sensorial studies
Document Type:
Academic journal
Article
File Description:
text
Language:
English
Author Affiliations:
Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy
Department of Management and Engineering, University of Padova, Vicenza, Italy
Department of Management and Engineering, University of Padova, Vicenza, Italy
ISSN:
0361-0926
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.26341216
Database:
PASCAL Archive
Further Information
In this article, multivariate extensions of the combination-based test statistics for the comparison of several treatments in the multivariate Randomized Complete Block designs are introduced in case of categorical response variables. Several tests for the multivariate Randomized Complete Block designs, including MANOVA procedure, are compared with the method proposed via a Monte Carlo simulation study. The method has also been applied to a real case study in the field of sensorial testing studies. Results suggest that in each experimental situation where normality of the supposed underlying continuous model is hard to justify and especially when errors have heavy-tailed distributions, the proposed nonparametric procedure can be considered as a valid solution.