Working group

of Ditzhaus

Together with my colleague Prof. Smaga from Poland we could extend our previous results on the multivariate coefficient of variation in various direction. Our preprint got now accepted by Scandinavian Journal of Statistics:

• Ditzhaus and Smaga. Inference for all variants of the multivariate coefficient of variation in factorial designs. Accepted by  Scandinavian Journal of Statistics (preliminary arXiv-preprint, arXiv:2301.12009, is online available).

In April  2024, Dirk Schomburg and Simon Mack joined our team. Welcome!

New progress in our DFG project on Survival Analysis. Merle´s paper about the RMST in factorial designs and a corresponing R package are published:

• GFDrmst: available on CRAN. This package consists multiple tests based on the restricted mean survival time (RMST) for general factorial designs as described in Munko et al. (2024, Stat. Med.) 

• Munko, Ditzhaus, Dobler, Genuneit (2024). RMST-based multiple contrast tests in general factorial designs. Statistics in Medicine. 2024; 1-18. doi: 10.1002/sim.10017 (Open Access)

A successful start in 2023 with three accepted papers:

• Matabuena, Félix, Ditzhaus, Vidal and Gude. Hypothesis testing for matched pairs with missing data by maximum mean discrepancy: An application to continuous glucose monitoring.  Accept by The American Statistician (preliminary arXiv-Version)
  • RKHS-procedure for complex missing data scenarios
• Dormuth, Liu, Xu, Pauly, Ditzhaus. A comparitive study to alternatives to the log-rank test. Accepted by Contemporary Clinical Trials  (prelininary arXiv-preprint)
  • Comparison of novel two-sample tests for time-to-event data when the hazards are not proportional
• Ditzhaus, Yu and Xu. Studentized Permutation Method for Comparing Restricted Mean Survival Times with Small Sample from Randomized Trials. Accepted by Statistics in Medicine (preliminary arXiv-preprint).
  • Two-sample test procedure and confidence intervalls for the restriced mean survival time when the sample size is small.