Blog

  Most statisticians know Sir Harold Jeffreys as the conceptual father and tireless promotor of the Bayesian hypothesis test. However, Jeffreys was also a prominent geophysicist. For instance, Jeffreys is credited with the discovery that the earth has a liquid core. Recently, I read Jeffreys’s 1929 book “The Future of the Earth”, which is a smaller and more accessible version…

WARNING: This post starts with two chess studies. They are both magnificent, but if you don’t play chess you might want to skip them. I thank Ulrike Fischer for creating the awesome LaTeX package “chessboard”. NB. The idea discussed here also occurs in Haaf et al. (2019), the topic of a previous post. The Bristol Theme The game of chess…

Some time ago I ran a twitter poll to determine what people believe is the best statistics book of all time. This is the result: The first thing to note about this poll is that there are only 26 votes. My disappointment at this low number intensified after I ran a control poll, which received more than double the votes:

  WARNING: This is a Bayesian perspective on a frequentist procedure. Consequently, hard-core frequentists may protest and argue that, for the goals that they pursue, everything makes perfect sense. Bayesians will remain befuddled. Also, I’d like to thank Richard Morey for insightful, critical, and constructive comments. In an unlikely alliance, Deborah Mayo and Richard Morey (henceforth: M&M) recently produced an…

An often voiced concern about p-value null hypothesis testing is that p-values cannot be used to quantify evidence in favor of the point null hypothesis. This is particularly worrisome if you conduct a replication study, if you perform an assumption check, if you hope to show empirical support for a theory that posits an invariance, or if you wish to…

Over the last couple of weeks several researchers campaigned for a new movement of statistical reform: To retire statistical significance. Recently, the pamphlet of the movement was published in form of a comment in Nature, and the authors, Valentin Amrhein, Sander Greenland, and Blake McShane, were supported by over 800 signatories. Retire Statistical Significance When reading the comment we agreed…

  Preprint: doi:10.31234/osf.io/wgb64 Abstract “Many statistical scenarios initially involve several candidate models that describe the data-generating process. Analysis often proceeds by first selecting the best model according to some criterion, and then learning about the parameters of this selected model. Crucially however, in this approach the parameter estimates are conditioned on the selected model, and any uncertainty about the model…