Trustworthy assessment of heterogeneous treatment effect estimator
Fuente:
arXiv
Saved in:
| Main Author: | Gao, Zijun |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A causal fused lasso for interpretable heterogeneous treatment effects estimation
by: Padilla, Oscar Hernan Madrid, et al.
Published: (2021)
by: Padilla, Oscar Hernan Madrid, et al.
Published: (2021)
Distilling heterogeneous treatment effects: Stable subgroup estimation in causal inference
by: Huang, Melody, et al.
Published: (2025)
by: Huang, Melody, et al.
Published: (2025)
Selective randomization inference for subgroup effects with continuous biomarkers
by: Gao, Zijun
Published: (2025)
by: Gao, Zijun
Published: (2025)
Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data
by: Karlsson, Rickard, et al.
Published: (2025)
by: Karlsson, Rickard, et al.
Published: (2025)
Variable importance measures for heterogeneous treatment effects
by: Hines, Oliver J., et al.
Published: (2022)
by: Hines, Oliver J., et al.
Published: (2022)
Estimation and inference of average treatment effects under heterogeneous additive treatment effect model
by: Lu, Xin, et al.
Published: (2024)
by: Lu, Xin, et al.
Published: (2024)
On min-Storey estimators for multiple testing and conformal novelty detection
by: Zijun, Gao, et al.
Published: (2026)
by: Zijun, Gao, et al.
Published: (2026)
Two-stage least squares with treatment-covariate interactions for treatment effect heterogeneity
by: Zhao, Anqi, et al.
Published: (2025)
by: Zhao, Anqi, et al.
Published: (2025)
Variable importance measures for heterogeneous treatment effects with survival outcome
by: Ziersen, Simon Christoffer, et al.
Published: (2024)
by: Ziersen, Simon Christoffer, et al.
Published: (2024)
Data fusion methods for the heterogeneity of treatment effect and confounding function
by: Yang, Shu, et al.
Published: (2020)
by: Yang, Shu, et al.
Published: (2020)
Statistical inference of heterogeneous treatment effects using semiparametric single-index model
by: Yu, Jichang, et al.
Published: (2025)
by: Yu, Jichang, et al.
Published: (2025)
Finding network effect of randomized treatment under weak assumptions for any outcome and any effect heterogeneity
by: Lee, Myoung-jae
Published: (2025)
by: Lee, Myoung-jae
Published: (2025)
Semi-supervised inference for treatment heterogeneity
by: Anniwaer, Yilizhati, et al.
Published: (2025)
by: Anniwaer, Yilizhati, et al.
Published: (2025)
Estimating heterogeneous treatment effects by W-MCM based on Robust reduced rank regression
by: Hieda, Ryoma, et al.
Published: (2024)
by: Hieda, Ryoma, et al.
Published: (2024)
Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data
by: Lipkovich, Ilya, et al.
Published: (2023)
by: Lipkovich, Ilya, et al.
Published: (2023)
Non-parametric assessment of the calibration of individualized treatment effects
by: Sadatsafavi, Mohsen, et al.
Published: (2025)
by: Sadatsafavi, Mohsen, et al.
Published: (2025)
Comment on "Generic machine learning inference on heterogeneous treatment effects in randomized experiments."
by: Imai, Kosuke, et al.
Published: (2025)
by: Imai, Kosuke, et al.
Published: (2025)
Augmented match weighted estimators for average treatment effects
by: Xu, Tanchumin, et al.
Published: (2023)
by: Xu, Tanchumin, et al.
Published: (2023)
Adaptive sample splitting for randomization tests
by: Zhang, Yao, et al.
Published: (2025)
by: Zhang, Yao, 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)
by: Zuo, Shuozhi, et al.
Published: (2026)
Increased risk of type I errors for detecting heterogeneity of treatment effects in cluster-randomized trials using mixed-effect models
by: Hyun, Noorie, et al.
Published: (2024)
by: Hyun, Noorie, et al.
Published: (2024)
Identification and estimation of mediational effects of longitudinal modified treatment policies
by: Gilbert, Brian, et al.
Published: (2024)
by: Gilbert, Brian, et al.
Published: (2024)
Doubly robust average treatment effect estimation for survival data
by: Lee, Byeonghee, et al.
Published: (2025)
by: Lee, Byeonghee, et al.
Published: (2025)
Differential recall bias in estimating treatment effects in observational studies
by: Bong, Suhwan, et al.
Published: (2023)
by: Bong, Suhwan, et al.
Published: (2023)
Modified treatment policy effect estimation with weighted energy distance
by: Jiang, Ziren, et al.
Published: (2023)
by: Jiang, Ziren, et al.
Published: (2023)
Facilitating heterogeneous effect estimation via statistically efficient categorical modifiers
by: Kowal, Daniel R.
Published: (2024)
by: Kowal, Daniel R.
Published: (2024)
On regional treatment effect assessment using robust MAP priors
by: Zhang, Xin, et al.
Published: (2026)
by: Zhang, Xin, et al.
Published: (2026)
A joint modeling approach to treatment effects estimation with unmeasured confounders
by: Lee, Namhwa, et al.
Published: (2024)
by: Lee, Namhwa, et al.
Published: (2024)
Efficient estimation of subgroup treatment effects using multi-source data
by: Wang, Guanbo, et al.
Published: (2024)
by: Wang, Guanbo, et al.
Published: (2024)
Efficient semiparametric estimation of marginal treatment effects with genetic instrumental variables
by: Patel, Ashish, et al.
Published: (2026)
by: Patel, Ashish, et al.
Published: (2026)
Estimating heterogeneous treatment effects with survival outcomes via a deep survival learner
by: Sun, Yuming, et al.
Published: (2026)
by: Sun, Yuming, et al.
Published: (2026)
Estimation and Inference for Causal Explainability
by: Zhang, Weihan, et al.
Published: (2025)
by: Zhang, Weihan, et al.
Published: (2025)
Multi-Study Causal Forest (MCF): A flexible framework for data borrowing in the presence of varying treatment effect heterogeneity
by: Venkatasubramaniam, Ashwini, et al.
Published: (2025)
by: Venkatasubramaniam, Ashwini, et al.
Published: (2025)
Bayesian analysis of regression discontinuity designs with heterogeneous treatment effects
by: Tao, Kevin, et al.
Published: (2025)
by: Tao, Kevin, et al.
Published: (2025)
Comment on "Sequential validation of treatment heterogeneity" and "Comment on generic machine learning inference on heterogeneous treatment effects in randomized experiments"
by: Chernozhukov, Victor, et al.
Published: (2025)
by: Chernozhukov, Victor, et al.
Published: (2025)
Double machine learning to estimate the effects of multiple treatments and their interactions
by: Xiang, Qingyan, et al.
Published: (2025)
by: Xiang, Qingyan, et al.
Published: (2025)
Efficient estimation of average treatment effects with unmeasured confounding and proxies
by: Ai, Chunrong, et al.
Published: (2025)
by: Ai, Chunrong, et al.
Published: (2025)
Nonparametric estimation of the total treatment effect with multiple outcomes in the presence of terminal events
by: Gronsbell, Jessica, et al.
Published: (2024)
by: Gronsbell, Jessica, et al.
Published: (2024)
Efficient estimation of longitudinal treatment effects using difference-in-differences and machine learning
by: Illenberger, Nicholas, et al.
Published: (2024)
by: Illenberger, Nicholas, et al.
Published: (2024)
Unified implementation and comparison of Bayesian shrinkage methods for treatment effect estimation in subgroups
by: Wolbers, Marcel, et al.
Published: (2026)
by: Wolbers, Marcel, et al.
Published: (2026)
Similar Items
-
A causal fused lasso for interpretable heterogeneous treatment effects estimation
by: Padilla, Oscar Hernan Madrid, et al.
Published: (2021) -
Distilling heterogeneous treatment effects: Stable subgroup estimation in causal inference
by: Huang, Melody, et al.
Published: (2025) -
Selective randomization inference for subgroup effects with continuous biomarkers
by: Gao, Zijun
Published: (2025) -
Robust estimation of heterogeneous treatment effects in randomized trials leveraging external data
by: Karlsson, Rickard, et al.
Published: (2025) -
Variable importance measures for heterogeneous treatment effects
by: Hines, Oliver J., et al.
Published: (2022)