Abstract
A quite important problem usually occurs in several multidimensional hypothesis testing problems when variables are correlated and their associated regression forms are different (linear, quadratic, exponential, general monotonic, etc.). In this framework the NonParametric Combination (NPC) of a finite number of dependent permutation tests is suitable to cover almost all real situations of practical interest since the dependence relations among partial tests are implicitly captured by the combining procedure itself without the need to specify them (Pesarin and Salmaso, Permutation Tests for Complex Data: Theory, Applications and Software. Wiley, Chichester, 2010). The goal of this paper is to investigate via Monte Carlo simulations the impact of the dependency structure on the possible significance of combined tests in case of ordered categorical responses. The results showed that an increasing level of correlation/association among responses negatively affects the power of combination-based multivariate permutation tests.
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Giancristofaro, R.A., Carrozzo, E., Cichi, I., Boatto, V., Barisan, L. (2014). The Influence of the Dependency Structure in Combination-Based Multivariate Permutation Tests in Case of Ordered Categorical Responses. 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_22
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DOI: https://doi.org/10.1007/978-1-4939-2104-1_22
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