Cover Image

Improving efficiency in transporting average treatment effects

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rudolph, Kara E., Williams, Nicholas T., Stuart, Elizabeth A., Diaz, Ivan
Format:	Preprint
Published:	2023
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Nonparametric estimation of an optimal treatment rule with fused randomized trials and missing effect modifiers
by: Williams, Nicholas, et al.
Published: (2025)

Modified treatment policies that depend on the natural history of treatment
by: Díaz, Iván, et al.
Published: (2026)

Identification and estimation of mediational effects of longitudinal modified treatment policies
by: Gilbert, Brian, et al.
Published: (2024)

Longitudinal Generalizations of the Average Treatment Effect on the Treated for Multi-valued and Continuous Treatments
by: Susmann, Herbert, et al.
Published: (2024)

crumble: A comprehensive framework for modern causal mediation analysis with intermediate confounding
by: Liu, Richard, et al.
Published: (2026)

Learning Optimal Dynamic Treatment Regimes from Longitudinal Data
by: Williams, Nicholas T., et al.
Published: (2024)

Studying continuous, time-varying, and/or complex exposures using longitudinal modified treatment policies
by: Hoffman, Katherine L., et al.
Published: (2023)

A novel decomposition to explain heterogeneity in observational and randomized studies of causality
by: Gilbert, Brian, et al.
Published: (2022)

Recanting twins: addressing intermediate confounding in mediation analysis
by: Vo, Tat-Thang, et al.
Published: (2024)

Transporting results from a trial to an external target population when trial participation impacts adherence
by: Ross, Rachael K., et al.
Published: (2025)

Transporting treatment effects from difference-in-differences studies
by: Renson, Audrey, et al.
Published: (2023)

Two-Step Targeted Minimum-Loss Based Estimation for Non-Negative Two-Part Outcomes
by: Williams, Nicholas T., et al.
Published: (2024)

Longitudinal weighted and trimmed treatment effects with flip interventions
by: McClean, Alec, et al.
Published: (2025)

Sensitivity analysis for principal ignorability violation in estimating complier and noncomplier average causal effects
by: Nguyen, Trang Quynh, et al.
Published: (2023)

Efficient estimation of longitudinal treatment effects using difference-in-differences and machine learning
by: Illenberger, Nicholas, et al.
Published: (2024)

Everything all at once: On choosing an estimand for multi-component environmental exposures
by: Rudolph, Kara E., et al.
Published: (2025)

Who Are We Missing? A Principled Approach to Characterizing the Underrepresented Population
by: Parikh, Harsh, et al.
Published: (2024)

Parameterising the effect of a continuous treatment using average derivative effects
by: Hines, Oliver J., et al.
Published: (2021)

Identification of complier and noncomplier average causal effects in the presence of latent missing-at-random (LMAR) outcomes: a unifying view and choices of assumptions
by: Nguyen, Trang Quynh, et al.
Published: (2023)

Computationally and statistically efficient estimation of time-smoothed counterfactual curves
by: Susmann, Herbert P., et al.
Published: (2025)

Efficient collaborative learning of the average treatment effect
by: Li, Sijia, et al.
Published: (2024)

Estimation and inference of average treatment effects under heterogeneous additive treatment effect model
by: Lu, Xin, et al.
Published: (2024)

Augmented match weighted estimators for average treatment effects
by: Xu, Tanchumin, et al.
Published: (2023)

A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference
by: Parikh, Harsh, et al.
Published: (2025)

Nonparametric inference for sublevel-set probabilities of conditional average treatment effect functions
by: Munch, Anders, et al.
Published: (2026)

Doubly robust average treatment effect estimation for survival data
by: Lee, Byeonghee, et al.
Published: (2025)

Identification and estimation of the conditional average treatment effect with nonignorable missing covariates, treatment, and outcome
by: Zuo, Shuozhi, et al.
Published: (2026)

Regularizing Extrapolation in Causal Inference
by: Arbour, David, et al.
Published: (2025)

Absolute average and median treatment effects as causal estimands on metric spaces
by: Shin, Ha-Young, et al.
Published: (2024)

Efficient estimation of average treatment effects with unmeasured confounding and proxies
by: Ai, Chunrong, et al.
Published: (2025)

One-step TMLE for weighted average treatment effects
by: Liu, Yang, et al.
Published: (2026)

Estimating average treatment effects when treatment data are absent in a target study
by: Wen, Lan, et al.
Published: (2025)

Non-parametric efficient estimation of marginal structural models with multi-valued time-varying treatments
by: Martin, Axel, et al.
Published: (2024)

Randomization-based confidence sets for the local average treatment effect
by: Aronow, P. M., et al.
Published: (2024)

Efficient estimation of the target population average treatment effect from multi-source data
by: Su, Zehao, et al.
Published: (2024)

A comparison of methods for estimating the average treatment effect on the treated for externally controlled trials
by: Wang, Huan, et al.
Published: (2024)

Optimally weighted average derivative effects
by: Hines, Oliver, et al.
Published: (2023)

Estimating the average treatment effect in cluster-randomized trials with misclassified outcomes and non-random validation subsets
by: Isenberg, Dane, et al.
Published: (2025)

Resampling-based confidence intervals and bands for the average treatment effect in observational studies with competing risks
by: Rühl, Jasmin, et al.
Published: (2023)

Randomization-based Z-estimation for evaluating average and individual treatment effects
by: Qu, Tianyi, et al.
Published: (2024)