Copertina

Validating Causal Message Passing Against Network-Aware Methods on Real Experiments

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Tan, Albert, Shirani, Sadegh, Nordlund, James, Bayati, Mohsen
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Methodology Econometrics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Causal Message Passing for Experiments with Unknown and General Network Interference
di: Shirani, Sadegh, et al.
Pubblicazione: (2023)

Higher-Order Causal Message Passing for Experimentation with Complex Interference
di: Bayati, Mohsen, et al.
Pubblicazione: (2024)

Can We Validate Counterfactual Estimations in the Presence of General Network Interference?
di: Shirani, Sadegh, et al.
Pubblicazione: (2025)

On Evolution-Based Models for Experimentation Under Interference
di: Shirani, Sadegh, et al.
Pubblicazione: (2025)

Cross-Validated Causal Inference: a Modern Method to Combine Experimental and Observational Data
di: Yang, Xuelin, et al.
Pubblicazione: (2025)

Estimating Total Effects in Bipartite Experiments with Spillovers and Partial Eligibility
di: Tan, Albert, et al.
Pubblicazione: (2025)

Experimental Design For Causal Inference Through An Optimization Lens
di: Zhao, Jinglong
Pubblicazione: (2024)

Graph Neural Networks for Causal Inference Under Network Confounding
di: Leung, Michael P., et al.
Pubblicazione: (2022)

Reevaluating Causal Estimation Methods with Data from a Product Release
di: Young, Justin, et al.
Pubblicazione: (2026)

Experimental Design under Network Interference
di: Viviano, Davide
Pubblicazione: (2020)

Design-Based and Network Sampling-Based Uncertainties in Network Experiments
di: Sakamoto, Kensuke, et al.
Pubblicazione: (2025)

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

Causal Panel Analysis under Parallel Trends: Lessons from a Large Reanalysis Study
di: Chiu, Albert, et al.
Pubblicazione: (2023)

Causal Inference for Experiments with Latent Outcomes: Key Results and Their Implications for Design and Analysis
di: Fu, Jiawei, et al.
Pubblicazione: (2025)

Causal Inference for Spatial Treatments
di: Pollmann, Michael
Pubblicazione: (2020)

Comparing Experimental and Nonexperimental Methods: What Lessons Have We Learned Four Decades After LaLonde (1986)?
di: Imbens, Guido, et al.
Pubblicazione: (2024)

Balancing Weights for Causal Mediation Analysis
di: Kawato, Kentaro
Pubblicazione: (2025)

Nonparametric Causal Decomposition of Group Disparities
di: Yu, Ang, et al.
Pubblicazione: (2023)

Heterogeneous Treatment Effects and Causal Mechanisms
di: Fu, Jiawei, et al.
Pubblicazione: (2024)

Estimating Program Participation with Partial Validation
di: Denteh, Augustine, et al.
Pubblicazione: (2025)

Quantifying the Internal Validity of Weighted Estimands
di: Poirier, Alexandre, et al.
Pubblicazione: (2024)

Does Regression Produce Representative Causal Rankings?
di: Lal, Apoorva
Pubblicazione: (2024)

Causal Inference in Counterbalanced Within-Subjects Designs
di: Ho, Justin, et al.
Pubblicazione: (2025)

Re-examining Granger Causality with Causal Bayesian Networks and Reichenbachs Principles
di: Adedayo, S. A.
Pubblicazione: (2025)

Granger Causality in Expectiles: an M-vine copula test
di: Fuentes-Martínez, Roberto, et al.
Pubblicazione: (2026)

When Do Treatment Changes Identify Causal Effects?
di: Huber, Martin
Pubblicazione: (2026)

Non-parametric Causal Inference in Dynamic Thresholding Designs
di: Ghosh, Aditya, et al.
Pubblicazione: (2025)

Relative Bias Under Imperfect Identification in Observational Causal Inference
di: Huang, Melody, et al.
Pubblicazione: (2025)

Estimating Causal Effects of Discrete and Continuous Treatments with Binary Instruments
di: Chernozhukov, Victor, et al.
Pubblicazione: (2024)

Randomization Tests in Switchback Experiments
di: Liu, Jizhou, et al.
Pubblicazione: (2026)

Covariate Adjustment in Stratified Experiments
di: Cytrynbaum, Max
Pubblicazione: (2023)

Synthetic Controls for Experimental Design
di: Abadie, Alberto, et al.
Pubblicazione: (2021)

Kernel Three Pass Regression Filter
di: Jat, Rajveer, et al.
Pubblicazione: (2024)

Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models
di: Davezies, Laurent, et al.
Pubblicazione: (2021)

Heterogeneous Responses to Continuous Treatments: A Cluster-Based Causal Framework
di: Cerqua, Augusto, et al.
Pubblicazione: (2024)

Design-Based Uncertainty for Quasi-Experiments
di: Rambachan, Ashesh, et al.
Pubblicazione: (2020)

Switchback Experiments under Geometric Mixing
di: Hu, Yuchen, et al.
Pubblicazione: (2022)

Distributionally Robust Synthetic Control: Ensuring Robustness Against Highly Correlated Controls and Weight Shifts
di: Koo, Taehyeon, et al.
Pubblicazione: (2025)

Valid Inference when Testing Violations of Parallel Trends for Difference-in-Differences
di: Mikhaeil, Jonas M., et al.
Pubblicazione: (2025)

Coupling Designs for Randomized Experiments with Complex Treatments
di: Cytrynbaum, Max, et al.
Pubblicazione: (2026)