1 citations · 1 across the 3 of their papers we have counts for
6 papers
Partial Identification Learning with Categorical Treatments for Individualized Treatment Rules
Johannes Hruza, Paweł Morzywołek, Jakob Zeitler +2
We develop a partial identification learning framework for individualized treatment rules (ITRs) with categorical treatments, outcomes, and instrumental variables. Rather than rely…
Modified treatment policies that depend on the natural history of treatment
Iván Díaz, Nicholas T. Williams, Paweł Morzywołek +1
Longitudinal modified treatment policies (LMTP) are a class of interventions that allow the definition, identification, and estimation of causal effects in general settings, such a…
Inference on Variable Importance for Treatment Effect Heterogeneity: Shapley Values and Beyond
Pawel Morzywolek, Peter B. Gilbert, Alex Luedtke
We provide an inferential framework to assess variable importance for heterogeneous treatment effects. This assessment is especially useful in high-risk domains such as medicine, w…
The risks of risk assessment: causal blind spots when using prediction models for treatment decisions
Nan van Geloven, Ruth H Keogh, Wouter van Amsterdam +12
Clinicians increasingly rely on prediction models to guide treatment choices. Most prediction models, however, are developed using observational data that include some patients who…
Risk-based decision making: estimands for sequential prediction under interventions
Kim Luijken, Paweł Morzywołek, Wouter van Amsterdam +14
Prediction models are used amongst others to inform medical decisions on interventions. Typically, individuals with high risks of adverse outcomes are advised to undergo an interve…
Orthogonal prediction of counterfactual outcomes
Stijn Vansteelandt, Paweł Morzywołek
Orthogonal meta-learners, such as DR-learner, R-learner and IF-learner, are increasingly used to estimate conditional average treatment effects. They improve convergence rates rela…