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Interpreting results of one-way bayesian ANOVA in JASP

Dear forum,

I would like to ensure that I correctly interpret and report the results of one-way bayesian ANOVA (different samples, not repeated measures). I attach an output of my analysis (using JASP and SPSS). My questions are:
1. If I read the output correctly, in JASP I get Bayes factor (BF10) 0.175. Given that it is < 0.33, can I say that this supports H0?
2. When I report my JASP analysis I say that the priors were based on cauchy distribution. This is what I understood from this paper: https://link.springer.com/article/10.3758/s13423-017-1323-7 Would it be correct statement?
3. For comparison, I ran the same analysis in SPSS (Jeffreys–Zellner–Siow method). in SPSS the Bayes factor is 0.022. Is the discrepancy between two programs because of different priors?

Thank you a lot,


  • EJEJ Posts: 461

    Dear Vadim,

    1. You have BF10 = 0.175. This means that that BF01 = 1/0.175 = 5.71, meaning that the data are about 5.7 times more likely under H0 than under H1. This is support in favor of H0. I should not that BF10 = 0.99 would also have constituted evidence for H0 (but only a smidgen).
    2. Yes, that is correct.
    3. Weird. You can check with BayesFactor. I'll discuss this with Richard too. I doubt SPSS gives the correct result, because that BF is very small indeed.


  • SPSS is in error, almost surely. It would require a prior scale of almost two to get that low a Bayes factor.

    Here's my check. This isn't exactly right, because it appears you have slightly different numbers in each group, but this is the only way I can just use the F statistic. It should be very close.

    Fstat = .540
    N = 25
    J = 3
    df1 = J - 1
    df2 = (N - 1) * J
    1 - pf(.540, df1, df2 )
    ### [1] 0.5850897
    ### P value checks out against SPSS
    bf = BayesFactor::oneWayAOV.Fstat(Fstat, N, J, simple = TRUE)
    ###       B10 
    ### 0.1730758 
    ### Agrees with JASP
    ### Check for a range of prior scales
    rscale = exp(seq(log(.1), log(2), len = 50))
    bfs = sapply(rscale, function(r)
      BayesFactor::oneWayAOV.Fstat(Fstat, N, J, simple = TRUE, rscale = r))
    plot(rscale, bfs, ty='l', log = "xy", ylab = "Bayes factor", xlab = "Prior scale", las = 1)
    ## Blue line is default
    abline(h = bf, col = "blue")
    abline(v = 1/2, col = "blue")
    ## Red line is SPSS - way out there.
    abline(h = .022, col = "red")
  • vadimvadim Posts: 2

    Thank you very much for your answers and great software!

    Thanked by 1EJ
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