From the 2 of 13 linked papers with an AI index.
5 papers · 1 filter
Adaptive Confidence Sets for Binary Regression without Design Smoothness
P. M. Aronow, Patrick Lopatto
We study honest adaptive confidence sets for the regression function in random-design binary regression under loss. Assuming only known bounds on…
On Rates Attainable under Random Design: A Negative Answer to a Problem of Robins
P. M. Aronow, Patrick Lopatto
The paper proves that in nonparametric regression with random design, the conjectured optimal convergence rate for estimating a constant conditional variance is unattainable, estab…
Minimax unbiased estimation for finite populations with bounded outcomes
P. M. Aronow, Patrick Lopatto
We study design-unbiased estimation of the finite-population total when each outcome satisfies known bounds . For any sampling design with inclu…
One-step TMLE for weighted average treatment effects
Yang Liu, Patrick Lopatto, Ivana Malenica
We consider Targeted Maximum Likelihood Estimation (TMLE) of weighted average treatment effects (WATEs), a class of causal estimands that reweight the covariate distribution using…
Randomization-based confidence sets for the local average treatment effect
P. M. Aronow, Haoge Chang, Patrick Lopatto
We consider the problem of generating confidence sets in randomized experiments with noncompliance. We show that a refinement of a randomization-based procedure proposed by Imbens…