Correlations are a popular analysis tool in psychology to examine the extent to which two variables are related. For example, one might be interested in whether there is a relationship between shoe size and height. But what if you want to explore the relationship between two variables whilst controlling for the effects of a third … Continue reading Bayesian Estimation of Partial Correlations
Category: Bayesian
The Polls Weren’t Wrong
TL;DR: Trump had a 28% chance to win. We shouldn't be surprised he won. I'm not going to comment on the political outcome of last week's US Presidential elections; enough ink---both pen-ink and eye-ink---has been spilled about that. What I am going to comment on though is the growing feeling the polls were wrong, and … Continue reading The Polls Weren’t Wrong
“Bayesian in 8 Easy Steps” Journal Club
I've been trying to organise an online journal club to discuss the papers suggested in Alexander Etz and colleagues' paper "How to become a Bayesian in 8 easy steps". Several people have filled out the Doodle poll expressing an interest, but unfortunately not everyone can make the same time. As such, I am afraid I … Continue reading “Bayesian in 8 Easy Steps” Journal Club
(Pesky?) Priors
When I tell people I am learning Bayesian statistics, I tend to get one of two responses: either people look at me blankly---"What's Bayesian statistics?"---or I get scorned for using such "loose" methods---"Bayesian analysis is too subjective!"1. This latter "concern" arises due to (what I believe to be a misunderstanding of) the prior: Bayesian analysis … Continue reading (Pesky?) Priors
Animating Robustness-Check of Bayes Factor Priors
Today I submitted a paper which contained some Bayesian analysis using Bayes factors (a default Bayesian t-test). As the test used a default prior on the effect size (a Cauchy distribution centred on zero with rate [r] = 0.707), I wanted to appease any reviewer concern that the final Bayes factor reported was some peculiarity … Continue reading Animating Robustness-Check of Bayes Factor Priors
Recruitment Order & Sequential Bayes Factors
One advantage of using Bayes factors (or any other form of Bayesian analysis) is the ability to engage in optional stopping. That is, one can collect some data, perform the critical Bayesian test, and stop data collection once a pre-defined criterion has been obtained (e.g., until "strong" evidence has been found in support of one … Continue reading Recruitment Order & Sequential Bayes Factors
Polls: Why sample size matters
The people of Scotland are currently deciding in an upcoming "Yes-No" referendum (this Thursday!) whether to leave the British Union and become an independent nation. As is typical around times of heightened political interest, media outlets are awash with polls attempting to predict the outcome. Recent polls have put the "No" response at about 52%, although this … Continue reading Polls: Why sample size matters