tag:blogger.com,1999:blog-7959705296201073323.post4236828012949752250..comments2023-02-24T11:14:00.053+01:00Comments on The Bayesian kitchen: Blending p-values and posterior probabilitiesAnonymoushttp://www.blogger.com/profile/09710797049914216414noreply@blogger.comBlogger1125tag:blogger.com,1999:blog-7959705296201073323.post-9245123006969572862014-02-13T20:24:51.661+01:002014-02-13T20:24:51.661+01:00PS: Thinking about it, my claim in the last paragr...PS: Thinking about it, my claim in the last paragraph, i.e. that this question requires a combination of Bayesian and frequentist ideas, is perhaps not correct.<br /><br />The whole question is in fact a question of false discovery rate, and therefore, you have the choice: you can either formalize it in an empirical Bayes style (like Efron, 2008), in which case you are allowing yourself to consider hypotheses as random variables having a well defined prior and posterior probability of being true; or in a purely classical frequentist manner (like Benjamini and Hochberg, 1995), in which case you talk only about an expected proportion of false discoveries among a collection of fixed hypotheses.<br /><br />Thus, you can be a die-hard frequentist and make sense of this question... but I personally find it helpful to adopt a joint frequentist and (empirical) Bayesian perspective on the problem.<br /><br />Concerning Regina Nuzzo's column, on the other hand, the figure mentions "plausibilities" of hypotheses, so it does sound rather Bayesian (even if cryptically so).Anonymoushttps://www.blogger.com/profile/09710797049914216414noreply@blogger.com