I need to answer that email about the revision! I'm on-board, but the email got buried in my inbox.

Or maybe youse guys data is much cleaner than mine.

Maybe my style of interactive debugging is archaic.

Sometimes I just want to know how many zeros and NAs there are in a field and I don't want to write a long dplyr chain to figure that out.

Joo and Chiong’s recent working paper provides a Gaussian approximation to the regret function that you can use with ✨any✨ asymptotically normal estimator. This means you can use the minimax-regret criteria with your favorite treatment effect estimators: diff-in-diff, ML estimators.

I know you were responding to @blasimon.bsky.social, but wanted to chime in to say I agree they are very strong parametric assumptions. We tried to spell that out as clearly as we could.

To help marketing reviewers and editors understand the untestable assumptions of causal inference methods, Dominik Papies, Peter Ebbes and I wrote this "menu" as part of our chapter on "Endogeneity and Causal Inference in Marketing". (Preprint: dx.doi.org/10.2139/ssrn...)

Maybe we should get out the vacuums?

bsky.app/profile/sste...

I made it home! Everyone was a little bleary-eyed on Monday. 🦅🦅🦅