Sarah Friedrich-Welz: 'Resampling-based inference for causal effect estimates in time-to-event data'

You are all invited to an exciting seminar at Biostats on Friday, December 13 @ 10:00. Please note the day and time!

Speaker: Sarah Friedrich-Welz, Chair for Mathematical Statistics and Artificial Intelligence in Medicine Institute for Mathematics, University of Augsburg

 Title: "Resampling-based inference for causal effect estimates in time-to-event data"

 Abstract: 

In observational studies with time-to-event outcomes subject to competing risks, the g-formula can be used to estimate a treatment effect in the presence of confounding factors. The construction of valid pointwise confidence intervals and time-simultaneous confidence bands for the causal risk difference, however, is complicated. A convenient solution is to approximate the asymptotic distribution of the corresponding stochastic process by means of resampling approaches. In this talk, we consider three different resampling methods, namely the classical nonparametric bootstrap, the influence function equipped with a resampling approach as well as a martingale-based bootstrap version, the so-called wild bootstrap. We compare these approaches with regard to asymptotic properties and based on simulation studies and demonstrate their usage in a data example.

Room: Biostat library (5.2.46)

For more information and to see the abstracts go to https://biostatistics.dk/seminars/

Unless otherwise stated, seminars will be held at CSS (det gamle Kommunehospital), Øster Farimagsgade 5, 1353 Copenhagen K, room 5.2.46. Tea will be served in the library of the section of Biostatistics half an hour before the seminar starts.