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Mathematical Sciences Colloquium by Maria Umlauft
Friday, Sep 16, 2016
2 p.m. - 3 p.m. Location: FN 1.202

Maria Umlauft

Statistics

Ulm University

Rank-based permutation approaches for nonparametric factorial designs

In our work, we develop an exact rank-based permutation test for factorial designs. Typical restrictions of standard methods for analysing such data are equal variances across groups, balanced sample sizes or normally distributed error terms. However, these assumptions are often not met in real data. One alternative is given by the well-known Wald-type statistic (WTS) in semiparametric models, which also yields to asymptotically exact results in cases of heteroscedasticity and no particular error distribution. Recently, a modified permutation test based on the WTS has been develop to improve its small sample properties, see Pauly et al. [1]. However, if ordinal or ordered categorial data are present, the classical parametric and semiparametric models show their limits, since calculated means are neither meaningful nor suitable. Consequently, the aim of our work is to extend the Waldtype permutation statistic (WTPS) to a rank-based WTPS and therefore to nonparametric factorial designs allowing for all kind of observations such as discrete, ordinal or count data. Despite the difficulty of dependencies it is shown that this rank-based approach is also approximately exact and consistent. The small sample behaviour of the nonparametric Wald-type permutation statistic is compared to other well-known techniques in an extensive simulation study.

Joint work with Frank Konietschke and Markus Pauly

References

Pauly, Brunner, Konietschke (2015): “Asymptotic permutation tests in general factorial designs”, Journal of the Royal Statistical Society. Series B (Statistical
Methodology), 77(2), pp. 461-473

Sponsored by the Department of Mathematical Sciences

 

Contact Info:
John Zweck, 972-883-4995
Questions? Email me.

Contact Info:
John Zweck, 972-883-6699
Questions? Email me.

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