(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)
This is an old one but i think there still may be interest in the topic. In this post, I explain how to think about stopping rules in Bayesian inference and why, from a Bayesian standpoint, it’s not cheating to run an experiment until you get statistical significance and then stop.
If the topic interests you, I recommend you read the main post (including the P.S.) and also the comments.
The post Stopping rules and Bayesian analysis appeared first on Statistical Modeling, Causal Inference, and Social Science.
Please comment on the article here: Statistical Modeling, Causal Inference, and Social Science
