Markovianity-Based Conditioning Depth Diagnostics for Hidden Confounding in Observational Datasets

Documenti analoghi

• Time-Varying Confounding Bias in Observational Geoscience with Application to Induced Seismicity
  di: Xiao, Yuchen, et al.
  Pubblicazione: (2025)
• Adjustment for Unmeasured Spatial Confounding in Settings of Continuous Exposure Conditional on the Binary Exposure Status: Conditional Generalized Propensity Score-Based Spatial Matching
  di: Kim, Honghyok, et al.
  Pubblicazione: (2022)
• Quantifying Robustness to Unmeasured Confounding in Time-Varying Treatment Confounder Settings: An Extension of E-value Approach
  di: Sium, Md. Niamul Islam
  Pubblicazione: (2026)
• Sensitivity Analysis for Quantiles of Hidden Biases in Matched Observational Studies
  di: Wu, Dongxiao, et al.
  Pubblicazione: (2023)
• Bayesian Inference for Epidemic Final Size Datasets with Hidden Underlying Household Structure
  di: Brooks, Joseph, et al.
  Pubblicazione: (2026)