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20232026
most citedWild Bootstrap for Counting Process-Based Statistics

1 citations · 1 across the 4 of their papers we have counts for

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5 papers · 1 filter

stat.ME2026

Generalized multivariate Mann-Whitney- tests and confidence regions for relative effects under random missingness

Dennis Dobler, Jörg-Tobias Kuhn, Lubna Amro +1

Marginal Mann-Whitney effects are widely used across various fields of research, and extensions of this estimand have been developed in many directions in statistical methodology.…

stat.ME2025

Inference in pseudo-observation-based regression using (biased) covariance estimation and naive bootstrapping

Simon Mack, Morten Overgaard, Dennis Dobler

The pseudo-observation method is regularly applied to time-to-event data. However, to date such analyses have relied on not formally verified statements or ad-hoc methods regarding…

stat.ME2023

Inference via Wild Bootstrap and Multiple Imputation under Fine-Gray Models with Incomplete Data

Marina T. Dietrich, Dennis Dobler, Mathisca C. M. de Gunst

Fine-Gray models specify the subdistribution hazards for one out of multiple competing risks to be proportional. The estimators of parameters and cumulative incidence functions und…

stat.ME20231 cited

Wild Bootstrap for Counting Process-Based Statistics

Marina T. Dietrich, Dennis Dobler, Mathisca C. M. de Gunst

The wild bootstrap is a popular resampling method in the context of time-to-event data analyses. Previous works established the large sample properties of it for applications to di…

stat.ME2023

Testing for patterns and structures in covariance and correlation matrices

Paavo Sattler, Dennis Dobler

Covariance matrices of random vectors contain information that is crucial for modelling. Specific structures and patterns of the covariances (or correlations) may be used to justif…