Saved in:
| Main Authors: | Sium, Md. Niamul Islam, Patwary, Mohammad Hridoy |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.00343 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quantifying Robustness to Unmeasured Confounding in Time-Varying Treatment Confounder Settings: An Extension of E-value Approach
by: Sium, Md. Niamul Islam
Published: (2026)
by: Sium, Md. Niamul Islam
Published: (2026)
Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding
by: Peña, Jose M.
Published: (2024)
by: Peña, Jose M.
Published: (2024)
Central limit theorem for the global clustering coefficient of random geometric graphs
by: Yuan, Mingao, et al.
Published: (2026)
by: Yuan, Mingao, et al.
Published: (2026)
Application of Propensity Score Models and Causal Estimators in Observational Studies under Model Misspecification
by: Das, Apu Chandra, et al.
Published: (2026)
by: Das, Apu Chandra, et al.
Published: (2026)
Comparing Causal Inference Methods for Point Exposures with Missing Confounders: A Simulation Study
by: Benz, Luke, et al.
Published: (2024)
by: Benz, Luke, et al.
Published: (2024)
Note on the Delta Method for Finite Population Inference with Applications to Causal Inference
by: Pashley, Nicole E.
Published: (2019)
by: Pashley, Nicole E.
Published: (2019)
When Is Causal Inference Possible? A Statistical Test for Unmeasured Confounding
by: Liu, Muye, et al.
Published: (2025)
by: Liu, Muye, et al.
Published: (2025)
Domain Adaptation Under MNAR Missingness
by: Stokes, Tyrel, et al.
Published: (2025)
by: Stokes, Tyrel, et al.
Published: (2025)
Estimating Average Causal Effects with Incomplete Exposure and Confounders
by: Wen, Lan, et al.
Published: (2025)
by: Wen, Lan, et al.
Published: (2025)
Graph Neural Networks for Causal Inference Under Network Confounding
by: Leung, Michael P., et al.
Published: (2022)
by: Leung, Michael P., et al.
Published: (2022)
Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders
by: Wang, Yuhao, et al.
Published: (2020)
by: Wang, Yuhao, et al.
Published: (2020)
Causal Inference with Categorical Unobserved Confounder via Mixture Learning
by: Saha, Aytijhya, et al.
Published: (2026)
by: Saha, Aytijhya, et al.
Published: (2026)
Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding
by: Zheng, Jiajing, et al.
Published: (2021)
by: Zheng, Jiajing, et al.
Published: (2021)
Nonlinear Causal Discovery with Confounders
by: Li, Chunlin, et al.
Published: (2023)
by: Li, Chunlin, et al.
Published: (2023)
Bayesian Sensitivity Analysis for Causal Estimation with Time-varying Unmeasured Confounding
by: Zou, Yushu, et al.
Published: (2025)
by: Zou, Yushu, et al.
Published: (2025)
Identifiable Deep Latent Variable Models for MNAR Data
by: Xie, Huiming, et al.
Published: (2026)
by: Xie, Huiming, et al.
Published: (2026)
Quantifying the Uncertainty of Imputed Demographic Disparity Estimates: The Dual-Bootstrap
by: Lu, Benjamin, et al.
Published: (2024)
by: Lu, Benjamin, et al.
Published: (2024)
Propensity Score Augmentation in Matching-based Estimation of Causal Effects
by: Ulloa-Pérez, Ernesto, et al.
Published: (2024)
by: Ulloa-Pérez, Ernesto, et al.
Published: (2024)
Statistical Inference for Regression with Imputed Binary Covariates with Application to Emotion Recognition
by: Lin, Ziqian, et al.
Published: (2024)
by: Lin, Ziqian, et al.
Published: (2024)
GST-UNet: A Neural Framework for Spatiotemporal Causal Inference with Time-Varying Confounding
by: Oprescu, Miruna, et al.
Published: (2025)
by: Oprescu, Miruna, et al.
Published: (2025)
Prediction-Powered Inference with Imputed Covariates and Nonuniform Sampling
by: Kluger, Dan M., et al.
Published: (2025)
by: Kluger, Dan M., et al.
Published: (2025)
Regression-Based Estimation of Causal Effects in the Presence of Selection Bias and Confounding
by: Hafer, Marlies, et al.
Published: (2025)
by: Hafer, Marlies, et al.
Published: (2025)
Nonparametric functional data classification and bandwidth selection in the presence of MNAR class variables
by: Mojirsheibani, Majid
Published: (2025)
by: Mojirsheibani, Majid
Published: (2025)
Causal Effect Estimation after Propensity Score Trimming with Continuous Treatments
by: Branson, Zach, et al.
Published: (2023)
by: Branson, Zach, et al.
Published: (2023)
Calibrated and Conformal Propensity Scores for Causal Effect Estimation
by: Deshpande, Shachi, et al.
Published: (2023)
by: Deshpande, Shachi, et al.
Published: (2023)
Comparative Study of Causal Discovery Methods for Cyclic Models with Hidden Confounders
by: Lorbeer, Boris, et al.
Published: (2024)
by: Lorbeer, Boris, et al.
Published: (2024)
Bayesian Causal Discovery with Cycles and Latent Confounders
by: Jin, Wei, et al.
Published: (2025)
by: Jin, Wei, et al.
Published: (2025)
Long-term Causal Inference Under Persistent Confounding via Data Combination
by: Imbens, Guido, et al.
Published: (2022)
by: Imbens, Guido, et al.
Published: (2022)
Propensity Score Propagation: A General Framework for Design-Based Inference with Unknown Propensity Scores
by: Heng, Siyu, et al.
Published: (2026)
by: Heng, Siyu, et al.
Published: (2026)
Improving Causal Inference with Measurement Errors in Exposures and Confounders: A New Method and Its Application to Air Pollution Exposure Assessment and Epidemiology
by: Kim, Honghyok
Published: (2024)
by: Kim, Honghyok
Published: (2024)
Identifying and Estimating Causal Direct Effects Under Unmeasured Confounding
by: Boileau, Philippe, et al.
Published: (2026)
by: Boileau, Philippe, et al.
Published: (2026)
Imputing Missing Values with External Data
by: Thiesmeier, Robert, et al.
Published: (2024)
by: Thiesmeier, Robert, et al.
Published: (2024)
Causal Concept Graphs in LLM Latent Space for Stepwise Reasoning
by: Meherab, Md Muntaqim, et al.
Published: (2026)
by: Meherab, Md Muntaqim, et al.
Published: (2026)
Comparing Propensity Score-Based Methods in Estimating the Treatment Effects: A Simulation Study
by: Poletto, Sara, et al.
Published: (2024)
by: Poletto, Sara, et al.
Published: (2024)
Bayesian Propensity Score-Augmented Latent Factor Models for Causal Inference with Time-Series Cross-Sectional Data
by: Liu, Licheng
Published: (2026)
by: Liu, Licheng
Published: (2026)
Double Robust Weighted Regression with Missing Confounders
by: Bagmar, Md. Shaddam Hossain, et al.
Published: (2026)
by: Bagmar, Md. Shaddam Hossain, et al.
Published: (2026)
Estimation and Inference for Causal Explainability
by: Zhang, Weihan, et al.
Published: (2025)
by: Zhang, Weihan, et al.
Published: (2025)
Sparse Causal Effect Estimation using Two-Sample Summary Statistics in the Presence of Unmeasured Confounding
by: Huang, Shimeng, et al.
Published: (2024)
by: Huang, Shimeng, et al.
Published: (2024)
Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based Estimators
by: Klaassen, Sven, et al.
Published: (2025)
by: Klaassen, Sven, et al.
Published: (2025)
Bayesian Inference for Confounding Variables and Limited Information
by: Scharfenaker, Ellis, et al.
Published: (2025)
by: Scharfenaker, Ellis, et al.
Published: (2025)
Similar Items
-
Quantifying Robustness to Unmeasured Confounding in Time-Varying Treatment Confounder Settings: An Extension of E-value Approach
by: Sium, Md. Niamul Islam
Published: (2026) -
Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding
by: Peña, Jose M.
Published: (2024) -
Central limit theorem for the global clustering coefficient of random geometric graphs
by: Yuan, Mingao, et al.
Published: (2026) -
Application of Propensity Score Models and Causal Estimators in Observational Studies under Model Misspecification
by: Das, Apu Chandra, et al.
Published: (2026) -
Comparing Causal Inference Methods for Point Exposures with Missing Confounders: A Simulation Study
by: Benz, Luke, et al.
Published: (2024)