14 citations · 35 across the 27 of their papers we have counts for
4 papers · 2 filters
RMST-based multiple contrast tests in general factorial designs
Merle Munko, Marc Ditzhaus, Dennis Dobler +1
Several methods in survival analysis are based on the proportional hazards assumption. However, this assumption is very restrictive and often not justifiable in practice. Therefore…
General multiple tests for functional data
Merle Munko, Marc Ditzhaus, Markus Pauly +2
While there exists several inferential methods for analyzing functional data in factorial designs, there is a lack of statistical tests that are valid (i) in general designs, (ii)…
Factorial survival analysis for treatment effects under dependent censoring
Takeshi Emura, Marc Ditzhaus, Dennis Dobler +1
Factorial analyses offer a powerful nonparametric means to detect main or interaction effects among multiple treatments. For survival outcomes, e.g. from clinical trials, such tech…
Inference for all variants of the multivariate coefficient of variation in factorial designs
Marc Ditzhaus, Łukasz Smaga
The multivariate coefficient of variation (MCV) is an attractive and easy-to-interpret effect size for the dispersion in multivariate data. Recently, the first inference methods fo…