Cover Image

Post-Experiment Decisions: The Dual Adjustments for Rollout and Downstream Optimizations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Guoxing, Yang, Dan, Zhang, Wei
Format:	Preprint
Published:	2026
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bridging Stratification and Regression Adjustment: Batch-Adaptive Stratification with Post-Design Adjustment in Randomized Experiments
by: Li, Zikai
Published: (2025)

Covariate Adjustment in Stratified Experiments
by: Cytrynbaum, Max
Published: (2023)

Covariate Adjustment in Randomized Experiments Motivated by Higher-Order Influence Functions
by: Zhao, Sihui, et al.
Published: (2024)

Sharp Bounds on the Variance of General Regression Adjustment in Randomized Experiments
by: Mikhaeil, Jonas M., et al.
Published: (2024)

Anytime-Valid Inference in Adaptive Experiments: Covariate Adjustment and Balanced Power
by: Molitor, Daniel, et al.
Published: (2025)

A Spectral Confounder Adjustment for Spatial Regression with Multiple Exposures and Outcomes
by: Prim, Shih-Ni, et al.
Published: (2025)

COADVISE: Covariate Adjustment with Variable Selection in Randomized Controlled Trials
by: Liu, Yi, et al.
Published: (2025)

Design-Based Causal Inference with Missing Outcomes: Missingness Mechanisms, Imputation-Assisted Randomization Tests, and Covariate Adjustment
by: Heng, Siyu, et al.
Published: (2023)

Data-Driven Adjustment for Multiple Treatments
by: LaPlante, Sara, et al.
Published: (2025)

Multivariate Adjustments for Average Equivalence Testing
by: Boulaguiem, Younes, et al.
Published: (2024)

A Connection Between Covariate Adjustment and Stratified Randomization in Randomized Clinical Trials
by: Zhang, Zhiwei
Published: (2024)

Evaluating Decision Rules Across Many Weak Experiments
by: Chou, Winston, et al.
Published: (2025)

Adjustment with Many Regressors Under Covariate-Adaptive Randomizations
by: Jiang, Liang, et al.
Published: (2023)

Automatic Variance Adjustment for Small Area Estimation
by: Wakefield, Jon, et al.
Published: (2026)

Conditional Adjustment in a Markov Equivalence Class
by: LaPlante, Sara, et al.
Published: (2023)

A Unified Approach to Covariate Adjustment for Survival Endpoints in Randomized Clinical Trials
by: Zhang, Zhiwei, et al.
Published: (2025)

When Does Interference Matter? Decision-Making in Platform Experiments
by: Johari, Ramesh, et al.
Published: (2024)

Learning Treatment Representations for Downstream Instrumental Variable Regression
by: Lin, Shiangyi, et al.
Published: (2025)

Improving Variance Estimation for Covariate Adjustment with Binary Outcomes
by: Lee, Kaitlyn, et al.
Published: (2026)

Covariate Adjustment for Wilcoxon Two Sample Statistic and Test
by: Lou, Zhilan, et al.
Published: (2026)

Robust Covariate Adjustment in Multi-Center Randomized Trials
by: Alene, Muluneh, et al.
Published: (2025)

Causal Inference under Interference: Regression Adjustment and Optimality
by: Fan, Xinyuan, et al.
Published: (2025)

A General Framework for Powerful Confounder Adjustment in Omics Association Studies
by: Roy, Asmita, et al.
Published: (2022)

Automated Analysis of Experiments using Hierarchical Garrote
by: Yu, Wei-Yang, et al.
Published: (2024)

Improving the Power of Bonferroni Adjustments under Joint Normality and Exchangeability
by: Hiltunen, Caleb, et al.
Published: (2026)

Optimal Integrative Estimation for Distributed Precision Matrices with Heterogeneity Adjustment
by: Sun, Yinrui, et al.
Published: (2024)

A General Form of Covariate Adjustment in Randomized Clinical Trials
by: Bannick, Marlena S., et al.
Published: (2023)

Task-tailored Pre-processing: Fair Downstream Supervised Learning
by: Sohn, Jinwon, et al.
Published: (2026)

Nonparametric Bayesian Adjustment of Unmeasured Confounders in Cox Proportional Hazards Models
by: Orihara, Shunichiro, et al.
Published: (2023)

False Discovery Rate Adjustments for Average Significance Level Controlling Tests
by: Armstrong, Timothy B.
Published: (2022)

Profile Bayesian Optimization for Expensive Computer Experiments
by: Kyger, Courtney, et al.
Published: (2025)

postcard: An R Package for Marginal Effect Estimation with or without Prognostic Score Adjustment
by: Jeppesen, Mathias Lerbech, et al.
Published: (2025)

Dynamic Treatment Regimes with Replicated Observations Available for Error-prone Covariates: a Q-learning Approach
by: Liu, Dan, et al.
Published: (2024)

Q-learning in Dynamic Treatment Regimes with Misclassified Binary Outcome
by: Liu, Dan, et al.
Published: (2024)

Covariate Adjustment for the Win Odds: Application to Cardiovascular Outcomes Trials
by: Scheidegger, Cyrill, et al.
Published: (2025)

Gaussianized Design Optimization for Covariate Balance in Randomized Experiments
by: Guo, Wenxuan, et al.
Published: (2025)

Expected Shortfall Regression via Optimization
by: Li, Yuanzhi, et al.
Published: (2026)

The RobinCar Family: R Tools for Robust Covariate Adjustment in Randomized Clinical Trials
by: Bannick, Marlena, et al.
Published: (2026)

Does Rerandomization Help Beyond Covariate Adjustment? A Review and Guide for Theory and Practice
by: Junior, Antônio Carlos Herling Ribeiro, et al.
Published: (2025)

Benchmarking Heritability Estimation Strategies Across 86 Configurations and Their Downstream Effect on Polygenic Risk Score Performance
by: Muneeb, Muhammad, et al.
Published: (2026)