2 citations · 2 across the 3 of their papers we have counts for
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Pulling back the curtain: the road from statistical estimand to machine-learning based estimator for epidemiologists (no wizard required)
Audrey Renson, Lina Montoya, Dana E. Goin +2
Epidemiologists increasingly use causal inference methods that rely on machine learning, as these approaches can relax unnecessary model specification assumptions. While deriving a…
Efficient estimation of longitudinal treatment effects using difference-in-differences and machine learning
Nicholas Illenberger, Iván Díaz, Audrey Renson
Difference-in-differences is based on a parallel trends assumption, which states that changes over time in average potential outcomes are independent of treatment assignment, possi…
Longitudinal Generalizations of the Average Treatment Effect on the Treated for Multi-valued and Continuous Treatments
Herbert Susmann, Nicholas T. Williams, Kara E. Rudolph +1
The Average Treatment Effect on the Treated (ATT) is a common causal parameter defined as the average effect of a binary treatment among the subset of the population receiving trea…