Saved in:
| Main Authors: | Sun, Hao, Munro, Evan, Kalashnov, Georgy, Du, Shuyang, Wager, Stefan |
|---|---|
| Format: | Preprint |
| Published: |
2021
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2103.11066 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Treatment Effects in Market Equilibrium
by: Munro, Evan, et al.
Published: (2021)
by: Munro, Evan, et al.
Published: (2021)
Switchback Experiments under Geometric Mixing
by: Hu, Yuchen, et al.
Published: (2022)
by: Hu, Yuchen, et al.
Published: (2022)
Treatment heterogeneity with right-censored outcomes using grf
by: Sverdrup, Erik, et al.
Published: (2023)
by: Sverdrup, Erik, et al.
Published: (2023)
Estimating Dynamic Marginal Policy Effects under Sequential Unconfoundedness
by: Lai, I-han, et al.
Published: (2026)
by: Lai, I-han, et al.
Published: (2026)
Neyman Jackknife: Design-Based Variance Estimation for Causal Inference under Interference
by: Park, Bryan, et al.
Published: (2026)
by: Park, Bryan, et al.
Published: (2026)
Qini Curves for Multi-Armed Treatment Rules
by: Sverdrup, Erik, et al.
Published: (2023)
by: Sverdrup, Erik, et al.
Published: (2023)
Non-parametric Causal Inference in Dynamic Thresholding Designs
by: Ghosh, Aditya, et al.
Published: (2025)
by: Ghosh, Aditya, et al.
Published: (2025)
Experimenting under Stochastic Congestion
by: Li, Shuangning, et al.
Published: (2023)
by: Li, Shuangning, et al.
Published: (2023)
Optimal Targeting in Dynamic Systems
by: Hu, Yuchen, et al.
Published: (2025)
by: Hu, Yuchen, et al.
Published: (2025)
PLRD: Partially Linear Regression Discontinuity Inference
by: Ghosh, Aditya, et al.
Published: (2025)
by: Ghosh, Aditya, et al.
Published: (2025)
Learning from a Biased Sample
by: Sahoo, Roshni, et al.
Published: (2022)
by: Sahoo, Roshni, et al.
Published: (2022)
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
by: Dandl, Susanne, et al.
Published: (2022)
by: Dandl, Susanne, et al.
Published: (2022)
Deep Learning of Continuous and Structured Policies for Aggregated Heterogeneous Treatment Effects
by: Zhang, Jennifer Y., et al.
Published: (2025)
by: Zhang, Jennifer Y., et al.
Published: (2025)
Minimax-Regret Sample Selection in Randomized Experiments
by: Hu, Yuchen, et al.
Published: (2024)
by: Hu, Yuchen, et al.
Published: (2024)
Noise-Induced Randomization in Regression Discontinuity Designs
by: Eckles, Dean, et al.
Published: (2020)
by: Eckles, Dean, et al.
Published: (2020)
Nonparametric Regression Discontinuity Designs with Survival Outcomes
by: Schuessler, Maximilian, et al.
Published: (2026)
by: Schuessler, Maximilian, et al.
Published: (2026)
Data Fusion for High-Resolution Estimation
by: Guan, Amy, et al.
Published: (2025)
by: Guan, Amy, et al.
Published: (2025)
Synthetic Difference in Differences
by: Arkhangelsky, Dmitry, et al.
Published: (2018)
by: Arkhangelsky, Dmitry, et al.
Published: (2018)
Optimal Treatment Allocations Accounting for Population Differences
by: Zhang, Wei, et al.
Published: (2025)
by: Zhang, Wei, et al.
Published: (2025)
Sequentially-Rerandomized Switchback Experiments
by: Zeng, Zhenghao, et al.
Published: (2026)
by: Zeng, Zhenghao, et al.
Published: (2026)
On Recoding Ordered Treatments as Binary Indicators
by: Rose, Evan K., et al.
Published: (2021)
by: Rose, Evan K., et al.
Published: (2021)
Evaluating the Effectiveness of Index-Based Treatment Allocation
by: Boehmer, Niclas, et al.
Published: (2024)
by: Boehmer, Niclas, et al.
Published: (2024)
Capturing Cumulative Disease Burden in Chronic Kidney Disease Outcome Trials: Area Under the Curve and Restricted Mean Time in Favor of Treatment Beyond Conventional Time-to-First Analysis
by: Sun, Jiren, et al.
Published: (2026)
by: Sun, Jiren, et al.
Published: (2026)
Leveraging Local Distributions in Mendelian Randomization: Uncertain Opinions are Invalid
by: Xu, Ziya, et al.
Published: (2024)
by: Xu, Ziya, et al.
Published: (2024)
Efficient Estimation of Average Treatment Effect on the Treated under Endogenous Treatment Assignment
by: Ghosh, Trinetri, et al.
Published: (2023)
by: Ghosh, Trinetri, et al.
Published: (2023)
Structural Causal Models for Extremes: an Approach Based on Exponent Measures
by: Bai, Shuyang, et al.
Published: (2025)
by: Bai, Shuyang, et al.
Published: (2025)
Learning Treatment Effects during Resource Allocation via Priority-Queue Randomization
by: Lee, JungHo, et al.
Published: (2026)
by: Lee, JungHo, et al.
Published: (2026)
Likelihood-ratio inference on differences in quantiles
by: Miller, Evan
Published: (2023)
by: Miller, Evan
Published: (2023)
Individualized Causal Effects under Network Interference with Combinatorial Treatments
by: Lu, Yunping, et al.
Published: (2026)
by: Lu, Yunping, et al.
Published: (2026)
Identification of Treatment Effects under Limited Exogenous Variation
by: Newey, Whitney K., et al.
Published: (2018)
by: Newey, Whitney K., et al.
Published: (2018)
Sharp Bounds for Treatment Effect Generalization under Outcome Distribution Shift
by: Asiaee, Amir, et al.
Published: (2026)
by: Asiaee, Amir, et al.
Published: (2026)
Cumulative Treatment Effect Testing under Continuous Time Reinforcement Learning
by: Zhang, Jiuchen, et al.
Published: (2026)
by: Zhang, Jiuchen, et al.
Published: (2026)
Treatment effect estimation under convergent network interference
by: Park, Bryan, et al.
Published: (2026)
by: Park, Bryan, et al.
Published: (2026)
Adaptive Neyman Allocation
by: Zhao, Jinglong
Published: (2023)
by: Zhao, Jinglong
Published: (2023)
Treatment effect estimation under covariate-adaptive randomization with heavy-tailed outcomes
by: Li, Hongzi, et al.
Published: (2024)
by: Li, Hongzi, et al.
Published: (2024)
Sequential Validation of Treatment Heterogeneity
by: Wager, Stefan
Published: (2024)
by: Wager, Stefan
Published: (2024)
Novel Knockoff Generation and Importance Measures with Heterogeneous Data via Conditional Residuals and Local Gradients
by: Mason, Evan, et al.
Published: (2025)
by: Mason, Evan, et al.
Published: (2025)
Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning
by: Dhir, Anish, et al.
Published: (2025)
by: Dhir, Anish, et al.
Published: (2025)
Fair Policy Learning under Bipartite Network Interference: Learning Fair and Cost-Effective Environmental Policies
by: Kim, Raphael C., et al.
Published: (2026)
by: Kim, Raphael C., et al.
Published: (2026)
Using Individualized Treatment Effects to Assess Treatment Effect Heterogeneity
by: Sechidis, Konstantinos, et al.
Published: (2025)
by: Sechidis, Konstantinos, et al.
Published: (2025)
Similar Items
-
Treatment Effects in Market Equilibrium
by: Munro, Evan, et al.
Published: (2021) -
Switchback Experiments under Geometric Mixing
by: Hu, Yuchen, et al.
Published: (2022) -
Treatment heterogeneity with right-censored outcomes using grf
by: Sverdrup, Erik, et al.
Published: (2023) -
Estimating Dynamic Marginal Policy Effects under Sequential Unconfoundedness
by: Lai, I-han, et al.
Published: (2026) -
Neyman Jackknife: Design-Based Variance Estimation for Causal Inference under Interference
by: Park, Bryan, et al.
Published: (2026)