Permutation Tests for Univariate and Multivariate Ordered Categorical Data

Authors

  • Fortunato Pesarin University of Padova, Italy
  • Luigi Salmaso University of Padova, Italy

DOI:

https://doi.org/10.17713/ajs.v35i2&3.378

Abstract

In this paper, we provide solutions for univariate and multivariate testing problems with ordered categorical variables by working within the nonparametric combination of dependent permutation tests (see Pesarin, 2001). Two applications and Monte Carlo simulations for power comparisons of NPC solutions to most competitors from the literature are shown.

References

Arboretti, G. R., Pesarin, F., and Salmaso, L. (2005). Nonparametric approaches for multivariate testing with mixed variables and for ranking on ordered categorical variables with an application to the evaluation of PhD programs. In S. Sawilowsky

(Ed.), Real Data Analysis. American Educational Research Association, Age Publishing (to appear).

Brunner, E., and Munzel, U. (2000). The nonparametric Behrens-Fisher problem: asymptotic theory and small-sample approximation. Biometrical Journal, 42, 17-25.

Cohen, A., Kemperman, J. H. B., Madigan, D., and Sakrowitz, H. B. (2003). Effective directed tests for models with ordered categorical data. Australian and New Zealand Journal of Statistics, 45, 285-300.

Joe, H. (1997). Multivariate Models and Dependence Concepts. London: Chapman & Hall.

Pesarin, F. (2001). Multivariate Permutation Test With Application to Biostatistics. Chichester: Wiley.

Silvapulle, M. J., and Sen, P. K. (2005). Constrained Statistical Inference, Inequality, Order, and Shape Restrictions. New York: Wiley.

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Published

2016-04-03

How to Cite

Pesarin, F., & Salmaso, L. (2016). Permutation Tests for Univariate and Multivariate Ordered Categorical Data. Austrian Journal of Statistics, 35(2&3), 315–324. https://doi.org/10.17713/ajs.v35i2&3.378

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Section

Articles