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Question about summary stats

Hi,

First of all, thanks for a great JASP course earlier this week!

I have two questions about the new summary stats module. I am not 100% sure how JASP calculates the BF for an existing correlation from just the sample size and the Pearson's r-value. Does this mean that for every sample of X and r-value of Y the BF is Z?

Also, could I use the summary stats module to create a qualitative meta-analysis? I was thinking about calculating the BF for correlations in a given domain and then calculating the percentage of them that exceed a BF=10 to assess the strength of evidence across studies. Do you think this would be a legitimate approach to go?

Thanks,
Daniel

Comments

  • Hi Daniel,

    Yes, that is correct: for the BF and the posterior distribution, r and N alone are sufficient. See http://arxiv.org/abs/1510.01188 for details.

    As far as the quantitative meta-analysis is concerned, I'd prefer to see all of the BFs; using a cut-off loses information. But otherwise, yes, these kinds of endeavors are what the module was meant for.

    Cheers,
    E.J.

  • Hi EJ,

    Thanks so much for your response and the link to the paper!

    If I may ask a quick follow up: for the quantitative meta how would you go about creating some kind of aggregate BF? So if I was comparing correlations in domain X with correlations in domain Y, how would I provide some kind of summary stat of the evidence (an aggregate BF)? Any suggestions for this?

    Best,
    Daniel

  • First, Richard Morey and Jeff Rouder have a paper on BF meta-analyses (2011 in PBR, a response to Bem). Second, are you interested in a BF for the difference in correlations?
    E.J.

  • Thanks! I will read that paper.

    Yes, I am interested in a BF for the difference in correlations!
    Best,
    Daniel

  • Ah yes. Well that requires a separate development. You could plot the two posteriors and eyeball them, but that is not a real test. We have it on our radar but it will take some time to get done.
    E.J.

  • Great. Thanks!

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