## The Butler, The Maid, And The Bayes Factor

This post is based on the example discussed in Wagenmakers et al. (in press). The Misconception Bayes factors are a measure of absolute goodness-of-fit or absolute pre- dictive performance. The Correction Bayes factors are a measure of relative goodness-of-fit or relative predictive performance. Model A may outpredict model B by a large margin, but this does not imply that model…

## Bayes Factors for Those Who Hate Bayes Factors

This post is inspired by Morey et al. (2016), Rouder and Morey (in press), and Wagenmakers et al. (2016a). The Misconception Bayes factors may be relevant for model selection, but are irrelevant for parameter estimation. The Correction For a continuous parameter, Bayesian estimation involves the computation of an infinite number of Bayes factors against a continuous range of different point-null…

## Popular Misconceptions About Bayesian Inference: Introduction to a Series of Blog Posts

“By seeking and blundering we learn.” – Johann Wolfgang von Goethe Bayesian methods have never been more popular than they are today. In the field of statistics, Bayesian procedures are mainstream, and have been so for at least two decades. Applied fields such as psychology, medicine, economy, and biology are slow to catch up, but in general researchers now view…

## A Personal Impression of the ASA Symposium on Statistical Inference: A World Beyond p<.05

I (Alex Etz) recently attended the American Statistical Association’s “Symposium on Statistical Inference” (SSI) in Bethesda Maryland. In this post I will give you a summary of its contents and some of my personal highlights from the SSI. The purpose of the SSI was to follow up on the historic ASA statement on p-values and statistical significance. The ASA…

## An Interactive App for Designing Informative Experiments

Bayesian inference offers the pragmatic researcher a series of perks (Wagenmakers, Morey, & Lee, 2016). For instance, Bayesian hypothesis tests can quantify support in favor of a null hypothesis, and they allow researchers to track evidence as data accumulate (e.g., Rouder, 2014). However, Bayesian inference also confronts researchers with new challenges, for instance concerning the planning of experiments. Within the…

## Redefine Statistical Significance Part X: Why the Point-Null Will Never Die

In our previous post, we discussed the paper “Abandon Statistical Significance”, which is a response to the paper “Redefine Statistical Significance” that has dominated the contents of this blog so far. The Abandoners include Andrew Gelman and Christian Robert, and on their own blogs they’ve each posted a reaction to our Bayesian Spectacles post. Below is a short response to…