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stat.ME2024★ 1 cited
Sensitivity of MCMC-based analyses to small-data removal
Tin D. Nguyen, Ryan Giordano, Rachael Meager +1
If the conclusion of a data analysis is sensitive to dropping very few data points, that conclusion might hinge on the particular data at hand rather than representing a more broad…
stat.ME2020★ 5 cited
An Automatic Finite-Sample Robustness Metric: When Can Dropping a Little Data Make a Big Difference?
Tamara Broderick, Ryan Giordano, Rachael Meager
Study samples often differ from the target populations of inference and policy decisions in non-random ways. Researchers typically believe that such departures from random sampling…