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20182020
most citedInferring median survival differences in general factorial designs via permutation tests

9 citations · 9 across the 3 of their papers we have counts for

collaborators

6 papers

stat.ME20209 cited

Inferring median survival differences in general factorial designs via permutation tests

Marc Ditzhaus, Dennis Dobler, Markus Pauly

Factorial survival designs with right-censored observations are commonly inferred by Cox regression and explained by means of hazard ratios. However, in case of non-proportional ha…

stat.ME2020

Permutation inference in factorial survival designs with the CASANOVA

Marc Ditzhaus, Arnold Janssen, Markus Pauly

We propose inference procedures for general nonparametric factorial survival designs with possibly right-censored data. Similar to additive Aalen models, null hypotheses are formul…

stat.ME2020

Permutation test for the multivariate coefficient of variation in factorial designs

Marc Ditzhaus, Łukas Smaga

New inference methods for the multivariate coefficient of variation and its reciprocal, the standardized mean, are presented. While there are various testing procedures for both pa…

math.ST2019

QANOVA: Quantile-based Permutation Methods For General Factorial Designs

Marc Ditzhaus, Roland Fried, Markus Pauly

Population means and standard deviations are the most common estimands to quantify effects in factorial layouts. In fact, most statistical procedures in such designs are built towa…

math.ST2019

Dependence correction of multiple tests with applications to sparsity

Marc Ditzhaus, Arnold Janssen

The present paper establishes new multiple procedures for simultaneous testing of a large number of hypotheses under dependence. Special attention is devoted to experiments with ra…

math.ST2018

On the consistency of adaptive multiple tests

Marc Ditzhaus, Arnold Janssen

Much effort has been done to control the "false discovery rate" (FDR) when hypotheses are tested simultaneously. The FDR is the expectation of the "false discovery proportion"…