MSP quantifies the minimum changes to analyst choices required to falsify a causal claim by making its confidence interval contain zero, providing information orthogonal to dispersion-based robustness summaries.
Tight certificates of ad- versarial robustness for randomly smoothed classifiers.Advances in Neural Information Processing Systems, 32, 2019
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Minimum Specification Perturbation: Robustness as Distance-to-Falsification in Causal Inference
MSP quantifies the minimum changes to analyst choices required to falsify a causal claim by making its confidence interval contain zero, providing information orthogonal to dispersion-based robustness summaries.