313 citations · 1.6k across the 58 of their papers we have counts for
34 papers · 1 filter
Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators
Lin Liu, Rajarshi Mukherjee, James M. Robins
The class of doubly-robust (DR) functionals studied by Rotnitzky et al. (2021) is of central importance in economics and biostatistics. It strictly includes both (i) the class of m…
Grace periods in comparative effectiveness studies of sustained treatments
Kerollos Nashat Wanis, Aaron L. Sarvet, Lan Wen +4
Researchers are often interested in estimating the effect of sustained use of a treatment on a health outcome. However, adherence to strict treatment protocols can be challenging f…
Causal and Counterfactual Views of Missing Data Models
Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser +1
It is often said that the fundamental problem of causal inference is a missing data problem -- the comparison of responses to two hypothetical treatment assignments is made difficu…
Using negative controls to identify causal effects with invalid instrumental variables
Oliver Dukes, David B. Richardson, Zachary Shahn +2
Many proposals for the identification of causal effects require an instrumental variable that satisfies strong, untestable unconfoundedness and exclusion restriction assumptions. I…
Randomized trials and their observational emulations: a framework for benchmarking and joint analysis
Issa J. Dahabreh, Jon A. Steingrimsson, James M. Robins +1
A randomized trial and an analysis of observational data designed to emulate the trial sample observations separately, but have the same eligibility criteria, collect information o…
Nonparametric identification is not enough, but randomized controlled trials are
P. M. Aronow, James M. Robins, Theo Saarinen +2
We argue that randomized controlled trials (RCTs) are special even among settings where average treatment effects are identified by a nonparametric unconfoundedness assumption. Thi…