Bayes factor for equality of correlation coefficients?
I’ve recently collected data from two experiments in which I am interested in the correlations between various measures. In some cases I expect there to be a correlation but in other cases I am actually expecting no correlation.
The R code in Wetzels & Wagenmakers (2012)'s paper "A default Bayesian hypothesis test for correlations and partial correlations” has been very helpful in expressing the likelihood that a coefficient does not differ from 0.
What I would like to show now is that the coefficients from the second experiment are “the same” as the ones from the first experiment. That is, I’d like to compare a model that assumes that both are identical with a model that allows two parameters and would want to know the relative evidence the data provide for those two models. So basically the Bayesian version of this test: http://vassarstats.net/rdiff.html
I have found this blog post that seems to provide a Bayesian alternative to R's
cor.test() function. It has JAGS code and I feel like there should be a way to do what I want to do in JAGS. So I'd look into that if there's no other way. I just wanted to ask here whether there's a more straightforward implementation of this somewhere that I can use?
Any pointers would be appreciated. Thanks!