#statstab #631 Prior Information in Frequentist Research Designs: The Case of Neyman’s Sampling Theory

Thoughts: Model-based v design-based problem. This should be discussed more.

#modelbased #designbased #sampling #priors #neyman #frequentist #bayesian

link.springer.com/article/10.1...

#statstab #630 A Tutorial on Distribution-Free Uncertainty Quantification Using Conformal Prediction

Thoughts: Conformal predictions are getting more popular.

#conformalprediction #frequentist #uncertainty #assumptions #distributions #tutorial

doi.org/10.1177/2515...

#BJA editorial by Sidebotham explaining why #anaesthesia research should rely on #Bayesian probabilities, rather than #frequentist probabilities, to achieve clinically meaningful #inference statistics.

https://www.bjanaesthesia.org/article/S0007-0912(26)00345-4/fulltext

Bayesian A/B testing gains traction in commercial experimentation platforms like GrowthBook, LaunchDarkly, and more. But are the benefits oversold? A deep dive reveals that Bayesian and frequentist approaches are more similar than widely believed. #A/Btesting #Bayesian #Frequentist

#statstab #624 Severe Testing:
Error Statistics versus Bayes Factor Tests

Thoughts: This seems to be the framework most NHST researchers are adopting.

#nhst #hypothesis #hypothesistesting #severetestting #equivalence #sesoi #methods #frequentist

doi.org/10.1086/736950