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Generating and Comparing Multivariate Ordinal Variables by Means of Permutation Tests

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Topics in Statistical Simulation

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 114))

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Abstract

In this paper we introduce a nonparametric approach based on permutation tests and nonparametric combination methodology (NPC) for testing for correlation in presence of multivariate categorical variables. After an overview of permutation inference and the NPC methodology, we discuss the nonparametric procedure and we show a simulation-based comparative study. In particular, we deal with simulations from multivariate ordinal random variables, in order to show the performance in terms of power when the assumption of normality is not satisfied. In this regard, we consider also a new proposal for generating samples from multivariate ordinal data.

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References

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Author information

Authors and Affiliations

  1. Department of Management and Engineering, University of Padova, Padua, Italy

    Eleonora Carrozzo & Luigi Salmaso

  2. Department of Economics, Management and Quantitative Methods, Università degli Studi di Milano, Milan, Italy

    Alessandro Barbiero & Pier Alda Ferrari

Authors
  1. Eleonora Carrozzo
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  2. Alessandro Barbiero
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  3. Luigi Salmaso
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  4. Pier Alda Ferrari
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Corresponding author

Correspondence to Luigi Salmaso .

Editor information

Editors and Affiliations

  1. St.Petersburg State University, St.Petersburg, Russia

    V.B. Melas

  2. University of Bologna, Rimini, Italy

    Stefania Mignani

  3. University of Bologna, Rimini, Italy

    Paola Monari

  4. University of Padova, Padova, Italy

    Luigi Salmaso

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Carrozzo, E., Barbiero, A., Salmaso, L., Ferrari, P.A. (2014). Generating and Comparing Multivariate Ordinal Variables by Means of Permutation Tests. In: Melas, V., Mignani, S., Monari, P., Salmaso, L. (eds) Topics in Statistical Simulation. Springer Proceedings in Mathematics & Statistics, vol 114. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2104-1_12

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