1 citations · 1 across the 2 of their papers we have counts for
2 papers
stat.ME2024
Approximations to worst-case data dropping: unmasking failure modes
Jenny Y. Huang, David R. Burt, Yunyi Shen +2
A data analyst might worry about generalization if dropping a very small fraction of data points from a study could change its substantive conclusions. Checking this non-robustness…
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…