Working group

of Ditzhaus

R-packages

• GFDrmtl: available on CRAN and as a SHINY-App. This package contains multiple tests based on the restricted mean time lost (RMTL) for competing risks data in general factorial designs as described in Munko et al. (2024, arXiv:2409.07917)
• GFDrmst: available on CRAN and as a SHINY-App. This package contains multiple tests based on the restricted mean survival time (RMST) for general factorial designs as described in Munko et al. (2024, Stat. Med.) 

Publications

• Munko, Ditzhaus, Dobler, Genuneit (2024). RMST-based multiple contrast tests in general factorial designs. Statistics in Medicine; 43(10): 1849-1866. doi: 10.1002/sim.10017 (Open Access)
• Munko (2024). Multiple Tests. Mitteilungen der Deutschen Mathematiker-Vereinigung; 32(1): 25-26. https://doi.org/10.1515/dmvm-2024-0011

Preprints

• Baumeister, Munko, Gladow, Ditzhaus, Chakarov and Pauly (2024). Early and Late Buzzards: Comparing Different Approaches for Quantile-based Multiple Testing in Heavy-Tailed Wildlife Research Data. (arXiv:2409.14926)
• Munko, Dobler and Ditzhaus (2024). Multiple tests for restricted mean time lost with competing risks data. (arXiv:2409.07917)
• Dobler and Munko (2024). Erratum on 'A Discontinuity Adjustment for Subdistribution Function Confidence Bands Applied to Right-Censored Competing Risks Data'. (arXiv:1702.01081)
• Munko and Dobler (2024). Conditional Delta-Method for Resampling Empirical Processes in Multiple Sample Problems. (arXiv:2408.10856)
• Munko, Ditzhaus, Pauly and Smaga (2024). Multiple Comparison Procedures for Simultaneous Inference in Functional MANOVA. (arXiv:2406.01242)
• Munko, Ditzhaus, Pauly, Smaga and Zhang (2023). General multiple tests for functional data. (arXiv:2306.15259)

Theses

• Master's thesis: "MultiFANOVA: Multiple Contrast Tests for Functional Data" (2022). This thesis was awarded by the DStatG as the best master's thesis.
• Bachelor's thesis: "Grenzwertsätze mit Anwendung in der Statistik" (2020).

• Biostatistics
• Factorial Designs
• Functional Data Analysis
• Multiple Testing
• Nonparametric Statistics
• Resampling Procedures
• Survival Analysis

Winter semester 2023/2024

Statistische Modellierung und Datenanalyse

Summer semester 2023

Statistik mit R E-Learning

• MultiFANOVA: Multiple Contrast Tests for Functional Data. German Probability and Statistics Days 2023 in Essen
• MultiFANOVA: Multiple Contrast Tests for Functional Data. Workshop on Nonparametric procedures for medical multisample comparison studies 2023 in Remagen
• Multiple Tests für funktionale Daten. DMV-Studierendenkonferenz 2023 in Bremen. This talk was awarded by the MPI MiS.
• MultiFANOVA: Multiple Contrast Tests for Functional Data (invited). Conference of the Central European Network 2023 in Basel
• Multiple Contrast Tests for the RMST in General Factorial Designs. Survival Analysis for Junior Researchers conference 2023 in Ulm
  
• Tests for functional data (invited). Open lecture 2023 in Poznań
• Surviving the multiple testing problem: RMST-based tests in general factorial designs (invited). CMStatistics 2023 in Berlin
• Surviving the multiple testing problem: RMST-based tests in general factorial designs. Biometric Colloquium 2024 in Lübeck
• Surviving the multiple testing problem: RMST-based tests in general factorial designs. Adaptive Designs and Multiple Testing Procedures Workshop 2024 in Ibiza
• Surviving the multiple testing problem: RMST-based tests in general factorial designs (invited). International Symposium on Nonparametric Statistics 2024 in Braga
• Surviving the multiple testing problem: RMST-based tests in general factorial designs. Fifth International Workshop on Statistical Analysis of Multi-outcome Data 2024 in Salzburg
• Surviving the multiple testing problem: RMST-based tests in general factorial designs (invited). World Congress in Probability and Statistics 2024 in Bochum
• Multiple RMTL-Based Tests for Competing Risks Data. 32nd International Biometric Conference 2024 in Atlanta