Nonparametric Multiple Contrast Tests
21. Januar 2011 - 15:52 – Stolpmann
Dr. Frank Konietschke
Department of Medical Statistics, University of Göttingen
Ort des Vortrages:
AM S1, Universitätsklinikum Schleswig-Holstein Campus Lübeck, Ratzeburger Allee 160, 23538 Lübeck
Uhrzeit:
10.00 Uhr s.t.
Datum:
4. Februar 2011 In practice, the assumption of normality of the data is often not fulfilled. Hence, there is a need for statistical procedures which can handle skewed distributions, as well as ordinal or categorical data.
In the literature, there are many nonparametric analysis of variance type procedures. But, the application of these procedures has disadvantages:
(i) The global hypothesis tested by analysis of variance (quadratic tests) is, in general, not the question of practitioners.
(ii) When the global hypothesis is rejected, then multiple comparison procedures must be applied, but the results are often not consistent with the global test.
(iii) Most nonparametric procedures cannot provide meaningful confidence intervals for the underlying effects.
In this talk, we will present some results from my PhD thesis, trying to solve these problems. We will discuss some new so-called relative contrast effects, which can be interpreted as the underlying effects of a nonparametric multiple testing procedure.
Almost surely consistent estimators and their multivariate distribution will be derived. We will present a new multiple testing approach and simultaneous confidence intervals for the effects.