Part 11: How robust is your finding? · Module 26
Would the finding survive a small nudge?
How Do You Assess Robustness?
A result you plan to act on should not fall apart the moment the data or the thresholds wobble a little. Robustness asks exactly that. The CNA ecosystem has a dedicated companion package for it called frscore , which scores how "fit-robust" your models are across a whole range of consistency and coverage thresholds, so you don't have to do it by hand and lose an afternoon.
frscored_cna() runs CNA again and again across a grid of thresholds, here from 1.0 down to 0.7 in steps of 0.1, and rewards the models that keep showing up. A pattern that reappears no matter how you turn the dials is one you can trust enough to put in front of a director without sweating.
What You Will Be Able to Do
- Explain what robustness means for a CNA finding.
- Run frscored_cna() across a range of thresholds.
- Judge whether a finding is steady enough to brief.