313 citations · 1.6k across the 58 of their papers we have counts for
12 papers · 1 filter
Potential Outcome and Decision Theoretic Foundations for Statistical Causality
Thomas S. Richardson, James M. Robins
In a recent paper published in the Journal of Causal Inference, Philip Dawid has described a graphical causal model based on decision diagrams. This article describes how single-wo…
Characterization of parameters with a mixed bias property
Andrea Rotnitzky, Ezequiel Smucler, James M. Robins
In this article we study a class of parameters with the so-called `mixed bias property'. For parameters with this property, the bias of the semiparametric efficient one step estima…
A unifying approach for doubly-robust regularized estimation of causal contrasts
Ezequiel Smucler, Andrea Rotnitzky, James M. Robins
We consider inference about a scalar parameter under a non-parametric model based on a one-step estimator computed as a plug in estimator plus the empirical mean of an estimator of…
Semiparametric Efficient Empirical Higher Order Influence Function Estimators
Lin Liu, Rajarshi Mukherjee, Whitney K. Newey +1
Robins et al. (2008, 2017) applied the theory of higher order influence functions (HOIFs) to derive an estimator of the mean of an outcome Y in a missing data model with Y miss…
Adaptive Estimation of Nonparametric Functionals
Lin Liu, Rajarshi Mukherjee, James Robins +1
We provide general adaptive upper bounds for estimating nonparametric functionals based on second order U-statistics arising from finite dimensional approximation of the infinite d…
Locally Robust Semiparametric Estimation
Victor Chernozhukov, Juan Carlos Escanciano, Hidehiko Ichimura +2
Many economic and causal parameters depend on nonparametric or high dimensional first steps. We give a general construction of locally robust/orthogonal moment functions for GMM, w…