6 citations · 6 across the 1 of their papers we have counts for
3 papers · 1 filter
Treatment Effect Estimation in Causal Survival Analysis: Practical Recommendations
Charlotte Voinot, Clément Berenfeld, Imke Mayer +2
The restricted mean survival time (RMST) difference offers an interpretable causal contrast to estimate the treatment effect for time-to-event outcomes, yet a wide range of availab…
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models
Imke Mayer, Julie Josse, Félix Raimundo +1
Inferring causal effects of a treatment, intervention or policy from observational data is central to many applications. However, state-of-the-art methods for causal inference seld…
Doubly robust treatment effect estimation with missing attributes
Imke Mayer, Erik Sverdrup, Tobias Gauss +3
Missing attributes are ubiquitous in causal inference, as they are in most applied statistical work. In this paper, we consider various sets of assumptions under which causal infer…