4 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
Bias of the additive hazard model in the presence of causal effect heterogeneity
Richard Post, Edwin van den Heuvel, Hein Putter
Hazard ratios are prone to selection bias, compromising their use as causal estimands. On the other hand, the hazard difference has been shown to remain unaffected by the selection…
The built-in selection bias of hazard ratios formalized
Richard Post, Edwin van den Heuvel, Hein Putter
It is known that the hazard ratio lacks a useful causal interpretation. Even for data from a randomized controlled trial, the hazard ratio suffers from built-in selection bias as,…
Beyond Conditional Averages: Estimating The Individual Causal Effect Distribution
Richard Post, Edwin van den Heuvel
In recent years, the field of causal inference from observational data has emerged rapidly. The literature has focused on (conditional) average causal effect estimation. When (rema…
Flexible machine learning estimation of conditional average treatment effects: a blessing and a curse
Richard Post, Isabel van den Heuvel, Marko Petkovic +1
Causal inference from observational data requires untestable identification assumptions. If these assumptions apply, machine learning (ML) methods can be used to study complex form…