5 citations · 7 across the 6 of their papers we have counts for
4 papers · 1 filter
Debiased machine learning for counterfactual survival functionals based on left-truncated right-censored data
Eric R. Morenz, Charles J. Wolock, Marco Carone
Learning causal effects of a binary exposure on time-to-event endpoints can be challenging because survival times may be partially observed due to censoring and systematically bias…
Stabilized Inverse Probability Weighting via Isotonic Calibration
Lars van der Laan, Ziming Lin, Marco Carone +1
Inverse weighting with an estimated propensity score is widely used by estimation methods in causal inference to adjust for confounding bias. However, directly inverting propensity…
Doubly robust inference via calibration
Lars van der Laan, Alex Luedtke, Marco Carone
Doubly robust estimators are widely used for estimating average treatment effects and other linear summaries of regression functions. While consistency requires only one of two nui…
Propensity Score Augmentation in Matching-based Estimation of Causal Effects
Ernesto Ulloa-Pérez, Marco Carone, Alex Luedtke
When assessing the causal effect of a binary exposure using observational data, confounder imbalance across exposure arms must be addressed. Matching methods, including propensity…