EJ
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- EJ
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Comments
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Other than saving the plots and editing them in different software (e.g., Adobe) I'm not sure. A good feature request for our GitHub page! EJ
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This is 0.19? If so, please report this on our GitHub page. I have seen this before and hoped we fixed it... EJ
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Hi Sophie, Do you mean Gauge R&R? This is available by activating our "Quality Control" module from the module list (blue + sign on the top right). Also, you might want to check out the examples in the JASP data library. Go to File -&g…
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Everybody is still on vacation :-) I'll schedule-send a reminder EJ
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Yes, best to upvote that issue if you want to put a little bit more pressure on this feature :-)
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We are working to make the setup more modular and more lean, but this will take some time (we have programmers working on this at the moment, however, so it is getting done). EJ
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This looks like a bug, and as such it is more appropriate for our programming team. Please post this issue on our GitHub page (for details see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/). BTW, the error might arise from the u…
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Correct! EJ
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Hi Luke, Well, the thing is this. If you want a more narrow prior, the BF will approach 1, as H1 will morph into H0 when the prior is infinitely peaked around 0, and you are comparing two identical hypotheses. So when I specify an informed prior, I …
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Hi Luke, The difference occurs because of the Jeffreys-Lindley paradox (https://link.springer.com/article/10.1007/s00407-022-00298-3). The estimation approaches do not involve H0, but the BF does. See also BayesianSpectacles.org, the posts on the (l…
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I've passed this on
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Dear Ashley19, What method does Minitab use? I would trust the bootstrap more. Cheers, E.J.
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Hi Mirjam, Our Bayesian Mann-Whitney expert is enjoying a holiday, but I have attended him to your post! Cheers, E.J.
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Soon, very soon...
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You could dispense with it, but you might need to appease the reviewers. Maybe this is useful? https://arxiv.org/abs/2406.19940 EJ
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We have not done mediation with Bayes factors yet (although see https://www.ejwagenmakers.com/2015/NuijtenEtAl2015.pdf). As a rough approximation for the moment I suggest using BIC. EJ
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This is more of a bug report I think. Could you post this issue on our GitHub page? (for details see https://jasp-stats.org/feature-requests-bug-reports/)
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Well the tables suggest that "position" and "distance" need to be included no matter what. This would not allow these to be tested, but it would narrow down the model space -- which could be what causes the numeric instability. S…
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Yes, the link would be good, and the data as well :-)
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Dear Indrani, Can you provide some more details?
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You don't need to add "Variety" as a between-subject factor. JASP already assumes each row is a single case.
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I've asked the team
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The error percentages are lower, right? Another thing you might try is add the components to the null model when you are sure that they should be included. JASP will then take that model as its point of departure, and this means that way fewer model…
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Dear Edie, I would start by reading up on papers concerning the Bayesian ANOVA. A list is available at https://jasp-stats.org/jasp-materials/#papersJASP, and one that is particularly relevant is van den Bergh, D., van Doorn, J., Marsman, M., Draws,…
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Hmm yes, would also be good to have I guess.
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Thanks, I've asked again (everybody is really busy as we are in the middle of testing a new version) EJ
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[under "Additional Options"]
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Yes, adding the random effects slows the current implementation down by a lot. I would try the Laplace approximation, which should be very fast. EJ
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https://static.jasp-stats.org/Nightlies/
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