The following is an email exchange with Hyunseung Kang on the nature of randomization inference. This was sparked by a couple of papers by David Freedman and David Lane: A Nonstochastic Interpretation of Reported Significance Levels; Significance Testing in a Nonstochastic Setting.
My good friend Joshua Loftus and I spent some 30 minutes to crack (at least we think we did!) a counterfactual inference made in a speech in the House of Commons in London in 1850 by Lord Palmerston, who was the Secretary of State for Foreign Affairs at the time.
This post is derived from my talk “Fisher, Statistics, and Randomization” in the Fisher in the 21st Century Conference organized by Fisher’s College, Gonville & Caius. In the first half of that talk, I tried to trace the origin of randomization.
I read a few interesting articles this week on the Fisher-Neyman debate on the foundation of hypothesis testing:
The Fisher, Neyman-Pearson Theories of Testing Hypotheses: One Theory or Two?. Rigorous uncertainty: why RA Fisher is important.
Over this Easter weekend, I wrote the following commentary for the reprinting on Leo Breiman’s paper “Statistical Modeling: The Two Cultures” by Observational Studies. This is partly based on a talk I gave last year.