313 citations · 403 across the 14 of their papers we have counts for
16 papers
Difference-in-Differences for Heterogeneous Effects of General Treatment Strategies Accounting for Time-Varying Covariates
Oliver Dukes, Zach Shahn, James Robins +1
We introduce a class of marginal Structural Nested Mean Models (mSNMMs) that enable modeling time-varying effect modification by a subset of covariates required as adjustment varia…
A note on the relation between one-step, outcome regression and IPW-type estimators of parameters with the mixed bias property
Andrea Rotnitzky, Ezequiel Smucler, James M. Robins
Bruns-Smith et al. (2025) established an algebraic identity between the one-step estimator and a specific outcome regression-type estimator for a class of parameters that forms a s…
Debiased Ill-Posed Regression
AmirEmad Ghassami, James M. Robins, Andrea Rotnitzky
In various statistical settings, the goal is to estimate a function which is restricted by the statistical model only through a conditional moment restriction. Prominent examples i…
On the asymptotic validity of confidence sets for linear functionals of solutions to integral equations
Ezequiel Smucler, James M. Robins, Andrea Rotnitzky
This paper examines the construction of confidence sets for parameters defined as linear functionals of a function of W and X whose conditional mean given Z and X equals the condit…
Variable elimination, graph reduction and efficient g-formula
F. Richard Guo, Emilija Perković, Andrea Rotnitzky
We study efficient estimation of an interventional mean associated with a point exposure treatment under a causal graphical model represented by a directed acyclic graph without hi…
A note on efficient minimum cost adjustment sets in causal graphical models
Ezequiel Smucler, Andrea Rotnitzky
We study the selection of adjustment sets for estimating the interventional mean under an individualized treatment rule. We assume a non-parametric causal graphical model with, pos…