3 citations · 4 across the 13 of their papers we have counts for
18 papers · 1 filter
The V-fold jackknife for semiparametric inference: variance estimation, confidence intervals, and simultaneous confidence bands
Yi Li, Ashkan Ertefaie, Mark van der Laan
For decades, the bootstrap has been a default tool for statistical inference because of its broad applicability and minimal analytic requirements. Although its validity is well und…
Nonparametric Estimation of Optimal Stochastic Just-In-Time Adaptive Interventions for Distal Outcomes
Jack M. Wolf, Nandita Mitra, Ashkan Ertefaie
Mobile and wearable technologies enable the delivery of just-in-time adaptive interventions (JITAIs) -- interventions that adapt treatment delivery to an individual's rapidly chang…
Optimal Treatment Policy Estimation for Recurrent Events with a Competing Terminal Event: An Instrumented Difference-in-Differences Approach
Ritoban Kundu, James Flory, Sean Hennessy +1
Learning reproducible and generalizable optimal treatment policies for chronic diseases requires large, representative populations with long-term follow-up. Administrative health d…
On Causal Inference for the Survivor Function
Benjamin R. Baer, Ashkan Ertefaie, Robert L. Strawderman
In this expository paper, we consider the problem of causal inference and efficient estimation for the counterfactual survivor function. This problem has previously been considered…
A structural nested rate model for estimating the effects of time-varying exposure on recurrent event outcomes in the presence of death
Daniel Mork, Robert L. Strawderman, Michelle Audirac +2
Assessing the causal effect of time-varying exposures on recurrent event processes is challenging in the presence of a terminating event. Our objective is to estimate both the shor…
Valid post-selection inference for penalized G-estimation
Ajmery Jaman, Ashkan Ertefaie, Michèle Bally +3
Understanding treatment effect heterogeneity is important for decision making in medical and clinical practices, or handling various engineering and marketing challenges. When deal…