I notice that JASP doesn't haven an option to do Spearman's correlations. Has this functionality simply not been implemented yet? Or is there some sense in which Spearman's correlations are inappropriate in a Bayesian context?

JASP does compute Spearman but not yet in a Bayesian framework. We have completed a Bayesian version of Kendall's tau (paper accepted pending minor revision) and hope to add this to JASP soon. Spearman might follow suit. Nonparametric analyses are a little more tricky within the Bayesian framework, but we do believe they are important and so we aim to develop them and include them in JASP.

It will not be in the next release (scheduled for a week or so after today) but it will probably be in the one after that. I would say it is a few months away.
Cheers,
E.J.

Meanwhile, you added Kendall's tau as an option for Baysian non-parametric correlation analysis. I'm not sure whether there are implemented statistics that adjust the tau coefficient for ties. Anyways, I'm interested in Bayesian Spearman correlation analysis. I assume that transforming my data into ranked data with ties and conducting a Bayesian Pearson correlation would not be equivalent to a Bayesian Spearman correlation!? Otherwise it would have been relatively simple to implement it into JASP. But please correct me if I'm wrong. Another minor remark: It would be nice to have an option to output the exact p values in a future Version of JASP.

About the exact p-values: check out next week's blog post (https://jasp-stats.org/blog/)
About Bayesian Spearman: no, unfortunately it is not that simple! For instance, if you have N=3 and the ranks perfectly correspond, conducting a test on the rank numbers gives a BF of infinity :-)

## Comments

333Dear researcher,

JASP does compute Spearman but not yet in a Bayesian framework. We have completed a Bayesian version of Kendall's tau (paper accepted pending minor revision) and hope to add this to JASP soon. Spearman might follow suit. Nonparametric analyses are a little more tricky within the Bayesian framework, but we do believe they are important and so we aim to develop them and include them in JASP.

Cheers,

E.J.

2Thanks for the quick response. I look forward to using the Bayesian Kendaull's tau once it has been implemented.

2Hi - I was just wondering if there was a timeframe for adding the Bayesian Kendall's tau? as I would be really interested in using it for my analysis.

Thank you

333It will not be in the next release (scheduled for a week or so after today) but it will probably be in the one after that. I would say it is a few months away.

Cheers,

E.J.

2EJ - does this mean that your paper is also imminent? I'm looking forward to reading it!

333The paper has a "minor revision from The American Statistician. We've almost completed the revision and I'm pretty confident. But you never know.

1Meanwhile, you added Kendall's tau as an option for Baysian non-parametric correlation analysis. I'm not sure whether there are implemented statistics that adjust the tau coefficient for ties. Anyways, I'm interested in Bayesian Spearman correlation analysis. I assume that transforming my data into ranked data with ties and conducting a Bayesian Pearson correlation would not be equivalent to a Bayesian Spearman correlation!? Otherwise it would have been relatively simple to implement it into JASP. But please correct me if I'm wrong. Another minor remark: It would be nice to have an option to output the exact p values in a future Version of JASP.

Thank you very much!

333Hi Philippe,

About the exact p-values: check out next week's blog post (https://jasp-stats.org/blog/)

About Bayesian Spearman: no, unfortunately it is not that simple! For instance, if you have N=3 and the ranks perfectly correspond, conducting a test on the rank numbers gives a BF of infinity :-)

Cheers,

E.J.

333That said, we actually have developed a Bayesian version of Spearman. Paper and implementation in JASP will hopefully follow soon.

Cheers,

E.J.