MSB
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Last I checked, all Bayesian analyses (ANOVA and regression) in JASP (which are done with BayesFactor) are actually liner-mixed models, so unbalanced designs should not be a problem.
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You're 100% right - BF10 = 1/BF01 I always prefer to write the actual values so that they are human-interpolate (which ever is larger than 1). e.g. it's easier to understand that H1 was 4.784 times less likely than H0 (BF01 = 4.784), than that H1 wa…
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I think it is more appropriate to explicitly note that the second "revered" test is post-hoc. If I were reviewing the paper, I would ask about this.
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This is a question of priors - your priors didn't expect a reverse congruency effect, so you didn't think of testing for one. This is the same as for NHST - if you did a 2-tail test, it would be significant, but in the opposite direction of what you…
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Yeah, but is it the logistical next step? (my wife advised against this joke, but I am my own man!)
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@EJ is there a time-line for including Bayesian logistic regression to JASP or R BayesFactor?
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No particular reason - just found that is makes it easier to do other calculation with it later (which I do sometimes). You can set the print to show the regular BFs: incBF <- inclusionBF(BF)print(incBF, logBF = F) Or you can extract them your…
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M.L., I've previously posted some of my custom code here in the forum (here>>) that includes a function for computing inclusion BFs.
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In JASP you can asses BFs from summary stats using the 'Summary Stats' module (in JASP's bar, when 'Common' is, hit the + sign).
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Sure, if I my data is dino-distributed that would be a problem. :D I was thinking more along the lines of skewed data and the like - where deviations from the norm are crucial for error-rate in NHST, but I would suspect less so for BFs.
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If you simply calculate the second (replication) BF only on the replication sample, you are using the same priors as used in the original BF, even though these should be updated to the posterior distribution estimated after the first sample. If I un…
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But if you implement model restrictions into JASP then I will have learned R for nothing! :p Thanks E.J.!
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Hi E.J., 3) If the (corrected prior odds) = (uncorrected prior odds)×correction.X, then applying (corrected BF) = (uncorrected BF)×correction.X would still result in the same posterior odds, which would still be equal to (uncorrected prior odds)×co…
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Thanks @EJ (and @richarddmorey , with whom I had a short back and forth with via email)!
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Hi EJ, Thanks! Will read!
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Or an upside down pentagram? Really scare the frequentists...
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Looking at your results, it would seem that this is due to a lack of effect for congruency - adding it to you ANOVA seems to hurt the overall explained variance, as can be seen in how the BF for a model containing both main effects is much weaker th…
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Hi EJ, I sure do like the subjective part of Bayesian inference - but I think I understand your point. Looking forward to all the awesome things coming out in future releases. Until then - thanks again! M
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If I understand you correctly, If I have a one-tailed hypothesis that rho is (-0.4), I would set the beta* prior to 0.4*2=0.8 and test for a negative correlation - this would give me a distribution with 50% of prior mass between 0.0-(-0.4) and 50% …
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Hi EJ, Thanks for your quick response. I'm not sure I understand what you mean by comparing posterior. I find that X1's beta is 0.5~, and i want to show that not only is this model better than one containing also X2, but also that X1's beta does …
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Thanks EJ!
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If i had known that being a psych-graduate would involve so much coding (matlab, e-prime, opensesame, R...) I might have re-considered 8-) Thanks!
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Hi All, Are there any plans to implement into JASP the methods Richard has described in the BayesFactor blog? Or should I add this to the list or reasons to finally learn R? M
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Hi EJ, Thank again for the detailed response. I think I got it - Thanks! M
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To my understanding, you were correct in your interpretation. In order to calculate the odds that the null is correct relative to the alternative, you would have to multiply the BF01 by the prior odds of both hypotheses being correct... (I haven't s…
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Hi EJ, Thanks for the quick response! I'm afraid I haven't quite understood the meaning of Beta prior widths, of how to set them... In accordance with your "trick", if I want to truncation my H0 to a max of r=0.6, would I set my Beta pri…
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Hi, I have a similar question about beta prior width. I have a measurement that I know cannot have a higher correlation than 0.6 (due to a known low reliability). How do I know what to set my beta prior width according to this prior knowledge? Tha…