Discuss how sensitivity analysis can be used in causal inference to assess the robustness of causal conclusions.
Instruction: Explain the role of sensitivity analysis in causal studies and provide an example of how it can be implemented.
Context: This examines the candidate’s ability to conduct thorough evaluations of causal claims, ensuring their reliability and robustness.
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Specify which assumption could fail and how that failure enters the effect estimate. Varying model inputs without a causal bias model is not automatically a sensitivity analysis for hidden confounding.
Suppose a UI comparison estimates a two-percentage-point activity-rate difference...