92 citations · 98 across the 4 of their papers we have counts for
5 papers
Optimally weighted average derivative effects
Oliver Hines, Karla Diaz-Ordaz, Stijn Vansteelandt
Weighted average derivative effects (WADEs) are nonparametric estimands with uses in economics and causal inference. Debiased WADE estimators typically require learning the conditi…
Variable importance measures for heterogeneous treatment effects
Oliver J. Hines, Karla Diaz-Ordaz, Stijn Vansteelandt
Motivated by applications in precision medicine and treatment effect heterogeneity, recent research has focused on estimating conditional average treatment effects (CATEs) using ma…
Parameterising the effect of a continuous treatment using average derivative effects
Oliver J. Hines, Karla Diaz-Ordaz, Stijn Vansteelandt
The average treatment effect (ATE) is commonly used to quantify the main effect of a binary treatment on an outcome. Extensions to continuous treatments are usually based on the do…
Demystifying statistical learning based on efficient influence functions
Oliver Hines, Oliver Dukes, Karla Diaz-Ordaz +1
Evaluation of treatment effects and more general estimands is typically achieved via parametric modelling, which is unsatisfactory since model misspecification is likely. Data-adap…
Robust Inference for Mediated Effects in Partially Linear Models
Oliver Hines, Stijn Vansteelandt, Karla Diaz-Ordaz
We consider mediated effects of an exposure, X on an outcome, Y, via a mediator, M, under no unmeasured confounding assumptions in the setting where models for the conditional expe…