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# MSB

MSB
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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).
Comment by MSB May 18
• Sure, if I my data is dino-distributed that would be a problem. 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.
Comment by MSB April 10
• 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 u…
Comment by MSB December 2017
• But if you implement model restrictions into JASP then I will have learned R for nothing! Thanks E.J.!
Comment by MSB November 2017
• 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)×…
Comment by MSB November 2017
• Thanks @EJ (and @richarddmorey , with whom I had a short back and forth with via email)!
Comment by MSB July 2017
• Hi EJ, Thanks! Will read!
Comment by MSB August 2016
• Or an upside down pentagram? Really scare the frequentists...
Comment by MSB August 2016
• 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…
Comment by MSB July 2016
• 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
Comment by MSB June 2016
• 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…
Comment by MSB June 2016
• 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…
Comment by MSB May 2016
• Thanks EJ!
Comment by MSB May 2016
• 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!
Comment by MSB April 2016
• 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
Comment by MSB April 2016
• Hi EJ, Thank again for the detailed response. I think I got it - Thanks! M
Comment by MSB March 2016
• 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 …
Comment by MSB March 2016
• 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 prior wi…
Comment by MSB March 2016
• 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? …
Comment by MSB March 2016