3 papers
stat.ME2026
Wild Bootstrap and Efron's Bootstrap for Debiased Cox Regression
Lena Schemet, Sarah Friedrich-Welz
Cox regression with Lasso penalization is widely used for variable selection in time-to-event data, but reliable coefficient inference after selection remains difficult. We investi…
stat.ME2026
Model-based bootstrap inference for Cox models after Lasso selection
Lena Schemet, Andreas Groll, Sarah Friedrich-Welz
Inference after variable selection in Cox regression is difficult because simple Wald-type intervals after selection can have poor finite-sample conditional coverage. We study a mo…
stat.ME2026
Statistical inference after variable selection in Cox models: A simulation study
Lena Schemet, Sarah Friedrich-Welz
Choosing relevant predictors is central to the analysis of biomedical time-to-event data. Classical frequentist inference, however, presumes that the set of covariates is fixed in…