Flexible Sensitivity Analysis for Observational Studies Without Observable Implications
Flexible Sensitivity Analysis for Observational Studies Without Observable Implications
Abstract A fundamental challenge in observational causal inference is that assumptions about unconfoundedness are not testable from data. Assessing sensitivity to such assumptions is therefore important in practice. Unfortunately, some existing sensitivity analysis approaches inadvertently impose restrictions that are at odds with modern causal inference methods, which emphasize flexible models …