:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, H. Sherry, Peng, Roger D.
Format:	Preprint
Published:	2025
Subjects:	Methodology
Online Access:	https://arxiv.org/abs/2501.04296
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Leveraging External Controls in Clinical Trials: Estimands, Estimation, Assumptions
by: Liu, Bo, et al.
Published: (2025)

Externally Valid Policy Evaluation Combining Trial and Observational Data
by: Ek, Sofia, et al.
Published: (2023)

$t$-Testing the Waters: Empirically Validating Assumptions for Reliable A/B-Testing
by: Jeunen, Olivier
Published: (2025)

Dependable Exploitation of High-Dimensional Unlabeled Data in an Assumption-Lean Framework
by: Ying, Chao, et al.
Published: (2026)

Testing the Missing Completely at Random Assumption for Functional Data
by: Ofner, Maximilian, et al.
Published: (2025)

Optimal Hold-Out Size in Cross-Validation
by: McAlinn, Kenichiro, et al.
Published: (2025)

Assumption-lean Inference for Network-linked Data
by: Li, Wei, et al.
Published: (2025)

Modeling Data Analytic Iteration With Probabilistic Outcome Sets
by: Peng, Roger D., et al.
Published: (2023)

Adaptive Data-Borrowing for Improving Treatment Effect Estimation using External Controls
by: Yang, Qinwei, et al.
Published: (2025)

Assumption Lean Regression
by: Berk, Richard A., et al.
Published: (2018)

cubble: An R Package for Organizing and Wrangling Multivariate Spatio-temporal Data
by: Zhang, H. Sherry, et al.
Published: (2022)

Transportability of Regression Calibration with External Validation Studies for Measurement Error Correction
by: Li, Zexiang, et al.
Published: (2026)

Graphical Modelling without Independence Assumptions for Uncentered Data
by: Andrew, Bailey, et al.
Published: (2024)

Assumption-Lean and Data-Adaptive Post-Prediction Inference
by: Miao, Jiacheng, et al.
Published: (2023)

Assumption-Lean Quantile Regression
by: Baklicharov, Georgi, et al.
Published: (2024)

Improving Transportability of Regression Calibration Under the Main/External Validation Study Design
by: Li, Zexiang, et al.
Published: (2025)

Imputing Missing Values with External Data
by: Thiesmeier, Robert, et al.
Published: (2024)

On Learning Causal Structures from Non-Experimental Data without Any Faithfulness Assumption
by: Lin, Hanti, et al.
Published: (2018)

Weighted Leave-One-Out Cross Validation
by: Pronzato, Luc, et al.
Published: (2025)

Data Sketching and Stacking: A Confluence of Two Strategies for Predictive Inference in Gaussian Process Regressions with High-Dimensional Features
by: Gailliot, Samuel, et al.
Published: (2024)

The Exchangeability Assumption for Permutation Tests of Multiple Regression Models: Implications for Statistics and Data Science Educators
by: Hardin, Johanna, et al.
Published: (2024)

Uncertainty in Bayesian Leave-One-Out Cross-Validation Based Model Comparison
by: Sivula, Tuomas, et al.
Published: (2020)

Relaxing the Assumption of Strongly Non-Informative Linkage Error in Secondary Regression Analysis of Linked Files
by: Bukke, Priyanjali, et al.
Published: (2025)

Reinforcing RCTs with Multiple Priors while Learning about External Validity
by: Finan, Frederico, et al.
Published: (2021)

Valid and Efficient Two-Stage Latent Subgroup Analysis with Observational Data
by: Luo, Yuanhui, et al.
Published: (2025)

Is External Information Useful for Data Fusion? An Evaluation before Acquisition
by: Dai, Guorong, et al.
Published: (2025)

WOW: WAIC-Optimized Gating of Mixture Priors for External Data Borrowing
by: Zhou, Shouhao, et al.
Published: (2025)

Sequential Sensitivity Analysis for Multiple Assumptions: A Framework for Understanding Racial Disparity in Police Use of Force
by: Leavitt, Thomas, et al.
Published: (2026)

Assumption Smuggling in Intermediate Outcome Tests of Causal Mechanisms
by: Blackwell, Matthew, et al.
Published: (2024)

Diagnostic Checking for Wasserstein Autoregression
by: Dai, Chenxiao, et al.
Published: (2025)

Improving Treatment Effect Estimation in Trials through Adaptive Borrowing of External Controls
by: Yang, Qinwei, et al.
Published: (2026)

Assumption-Lean Differential Variance Inference for Heterogeneous Treatment Effect Detection
by: Boileau, Philippe A., et al.
Published: (2025)

Contrasting Identifying Assumptions of Average Causal Effects: Robustness and Semiparametric Efficiency
by: Gorbach, Tetiana, et al.
Published: (2021)

Sequential Bootstrap for Out-of-Bag Error Estimation: A 100-Seed Replication Study and Variance-Structure Analysis
by: Peng, Cheng
Published: (2025)

Bayesian Clustering Prior with Overlapping Indices for Effective Use of Multisource External Data
by: Lu, Xuetao, et al.
Published: (2024)

Prior-Posterior Derived-Predictive Consistency Checks for Post-Estimation Calculated Quantities of Interest (QOI-Check)
by: Sennhenn-Reulen, Holger
Published: (2024)

Calibrated Model Criticism Using Split Predictive Checks
by: Li, Jiawei, et al.
Published: (2022)

Chasing Shadows: How Implausible Assumptions Skew Our Understanding of Causal Estimands
by: Vansteelandt, Stijn, et al.
Published: (2024)

Stress-Testing Assumptions: A Guide to Bayesian Sensitivity Analyses in Causal Inference
by: Oganisian, Arman
Published: (2026)

Assumption violations in causal discovery and the robustness of score matching
by: Montagna, Francesco, et al.
Published: (2023)