Computational Statistics

AG JProf. Sarah Friedrich

The methodological research of the working group “Computational Statistics” focuses on resampling- and permutation-approaches, particularly in settings with dependent data. These comprise, e.g., repeated measures and multivariate data. A further interest lays in observational and registry studies with survival data, where valid methods for causal effect estimates are needed. One major aim in this context is to investigate the applicability of different resampling schemes for deriving confidence intervals and time-simultaneous confidence bands for causal effect estimates in survival data subject to competing risks.

The methodological developments are motivated by close cooperations with clinical partners. The developed methods are made available for a wide audience by publishing freely available R-packages.

  1. GFD: Tests for General Factorial Designs
  2. rankFD: Rank-Based Tests for General Factorial Designs
  3. MANOVA.RM: Analysis of Multivariate Data and Repeated Measures Designs
  4. rankMANOVA: Rank-Based Tests for Multivariate Data in Nonparametric Factorial Designs
  5. mdir.logrank: Multiple-direction logrank test
[Translate to Englisch:] Nahaufnahme einer Computer-Tastatur

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Junior-Prof. Dr. Sarah Friedrich

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