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Activity Number: 297 - Advances in Nonparametric Testing
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract #322623 View Presentation
Title: Stratified Permutation Tests for Dependent Data
Author(s): Luigi Salmaso* and Rosa Arboretti and Eleonora Carrozzo
Companies: University of Padova and University of Padova and University of Padova
Keywords: Mixed data ; Resampling ; Multivariate data ; Categorical data

In recent years permutation testing methods have increased both in number of applications and in solving complex multivariate problems. Permutation tests are essentially of an exact nonparametric nature in a conditional context where conditioning is on the pooled observed data set which is generally a set of sufficient statistics in the null hypothesis. There are many complex multivariate problems which are difficult to solve outside the conditional framework and in particular outside the nonparametric combination (NPC) of dependent permutation tests method. We discuss and apply this method in the context of stratified experiments or observational studies and prove that it is effective and robust also compared with some competitor from the literature. Moreover, for a given number of subjects, when the number of variables diverges and the noncentrality parameter of the combined test diverges, then the power of permutation combination-based tests converges to one.

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