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Ranking of Multivariate Populations
A Permutation Approach with Applications
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Book Description
Ranking of Multivariate Populations: A Permutation Approach with Applications presents a novel permutation-based nonparametric approach for ranking several multivariate populations. Using data collected from both experimental and observation studies, it covers some of the most useful designs widely applied in research and industry investigations, such as multivariate analysis of variance (MANOVA) and multivariate randomized complete block (MRCB) designs.
The first section of the book introduces the topic of ranking multivariate populations by presenting the main theoretical ideas and an in-depth literature review. The second section discusses a large number of real case studies from four specific research areas: new product development in industry, perceived quality of the indoor environment, customer satisfaction, and cytological and histological analysis by image processing. A web-based nonparametric combination global ranking software is also described.
Designed for practitioners and postgraduate students in statistics and the applied sciences, this application-oriented book offers a practical guide to the reliable global ranking of multivariate items, such as products, processes, and services, in terms of the performance of all investigated products/prototypes.
Table of Contents
Theory and Methods
Introduction and Motivation
Some Guideline Examples
Formalization of the Problem and General Solution
Literature Review of the Ranking Problem
Specificities and Advantages of the Permutation Approach for the Multivariate Ranking Problem
Multivariate Ranking and Quality Improvement
References
Permutation Tests and Nonparametric Combination Methodology
Introduction to Permutation Tests
Multivariate Permutation Tests and Nonparametric Combination Methodology
Hypothesis Testing for Curve Comparison
Some Properties of Univariate and Multivariate Permutation Tests
References
A Permutation Approach for Ranking of Multivariate Populations
Set-Up of the Multivariate Ranking Problem
Some Monte Carlo Simulation Studies to Validate the Ranking Methods for Multivariate Populations
References
Software Tools, Applications, and Case Studies
The Software Nonparametric Combination Global Ranking
Integrating R and PHP in a Web App Framework
User Registration and Input/Output Management
NPC Global Ranking
References
Applications in New Product Development in Industry
A One-Way MANOVA Dose–Response Experiment
Multivariate Repeated Measures Experiments for NPD
Sensory Test: ST Analysis
The Ranking Approach on the Issue of Consumer Relevance in NPD
Conclusion
References
Subjective Evaluations and Perceived Quality of the Indoor Environment
Evaluation of Indoor Environmental Conditions in Educational Buildings
Evaluation of Indoor Environment Conditions in Classrooms
Measured and Perceived Indoor Environmental Quality at a Hospital
References
Evaluating Customer Satisfaction in Public and Private Services
A Survey on Job Satisfaction of PhD Graduates from the University of Ferrara
Performances and Perceived Quality of Services Delivered by Italian Public Administrations
Customer Satisfaction on Ski Teaching Service: The S.E.S.T.O. Survey
Customer Satisfaction Evaluation of Tourist Facilities: The Sesto Nature Survey Case Study
A Survey of the Potential of the Passito Wine Market
A Longitudinal Survey to Evaluate Perception of Malodours
Evaluation of Customer Satisfaction on Public Transport Services
References
Cytological and Histological Analysis by Image Processing: The Ranking Approach
Ranking of Estradiol Exposures on Intracellular Calcium Concentration in Bovine Brain–Derived Endothelial Cells
Ranking of Trophic Effects from Estrogen Exposure of Primary Cell Cultures from Fetal Bovine Cerebellum
Ranking of Storing Conditions in the Tanning Industry to Preserve Bovine Skin
References
Index
Author(s)
Biography
Authors
Livio Corain, PhD, is an assistant professor of statistics in the Department of Management and Engineering at the University of Padua.
Rosa Arboretti, PhD, is an assistant professor of statistics in the Department of Civil, Environmental and Architectural Engineering at the University of Padua.
Stefano Bonnini, PhD, is an assistant professor of statistics in the Department of Economics and Management at the University of Ferrara.
Contributors
Luigi Salmaso, PhD, is a full professor of statistics in the Department of Management and Engineering at the University of Padua.
Eleonora Carrozzo is a PhD student in managerial engineering in the Department of Management and Engineering at the University of Padua.