EJ
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- EJ
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Yeah this should not happen. It may be an issue that we've already resolved. Advice: 1. Please post the issue on our GitHub page, so the team can take a look (see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/) 2. A new version o…
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Hi Herry, * It may help if you select "compare to best model" * Let's break this down. Model A beats the null model by a tremendous amount. Model B actually does worse than the null model. Model A + B outpredicts the null model by a lot, …
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So the prior odds have been adjusted according to the Westfall formula. If you multiply this by the uncorrected "regular" BF you will get the posterior odds, which you can interpret as a "corrected" BF.
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Yes, that could in general be the case, although your specific example looks like a ratio scale. Of course you may be interested in an underlying psychological process that has a monotonic relation to the number of words; in this case an analysis as…
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Hi DJ, Unfortunately, this cannot be done yet. We are working on a comprehensive solution for editing all plots, but that will take a while to get done (we have to re-program all of our figures, and that's just the start). Cheers, E.J.
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Hi Mila, If you have accuracy data, then for a single individual you can use the binomial, for which the CI respects the bound. However, I assume that you have multiple individuals, and you analyze the proportion correct across subjects. You can us…
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yeah, taking that interrelationship into account would be best but I am not sure it is worth the trouble E.J.
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Hi Supermario, * Ah, yes, swapping the orders is counterbalancing -- I was confused because you added "randomly", but now I realize you meant to convey that the assignment to conditions was random. * Yes, four choices, that complicates th…
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Well I think you predict: 1. a main effect of material 2. no main effect of color 3. no interaction between material and color These predictions are straightforward to test with the standard output. I am not sure what the standard theory says about…
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Hmm. It seems that you can use three separate rank-based correlations between questionnaire score and number of fixations?
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Yes this is not trivial. The functionality we offer is taken from Merlise Clyde's BAS package. The documentation of that package will refer to a paper by Liang et al. for details. Let me look it up...here it is: @ARTICLE{LiangEtAl2008, AUTHOR = …
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Hi Boo Sorry for my tardy reply. So you have used your pilot data to come up with a more informed prior -- note: this does assume that you are confident that H1 holds in your pilot data set. You are trying to construct a prior on effect size under …
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Dear Supermario, Sorry for my tardy reply. Here are my thoughts: 1. With "randomly counterbalanced" do you mean "counterbalanced" or "randomly determined"? Even if it was counterbalanced, you may get a more diagnostic …
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Great question (and sorry for the tardy reply). We are currently working on this! It is not in JASP yet. Cheers, E.J.
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Dear Peter, Sorry for the tardy reply. Let me explain my reasoning. In early work, we would specify a directional hypothesis and use that both for BFs and for effect sizes. This is consistent and sensible. So why have we started to use a two-sided …
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I looked at GitHub and see that you are now in conversation with the team. Hope this is resolved quickly. E.J.
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In principle this should not be a problem, but I suspect that situations such as these require the data to be in long format. We are working to make that happen but we're not there yet. Good point this; you could post this issue on our GitHub page s…
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Hi Luke19, Sorry for the tardy reply. We are working on papers that explain these things. One of them has appeared already, and you can find it on https://jasp-stats.org/jasp-materials/ and then https://osf.io/ahhdr/ Cheers, E.J.
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Yes, that's fine. But the effect is not small! So I would push back here. You have a medium effect size with a medium-to-large sample size. The result of that combination is displayed in the prior-posterior plot. Clearly an effect size of 0 is not s…
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Dear MinaS, We can help you out but in order to do so effectively please post the issue on our GitHub page (for details see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/). Cheers, E.J.
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Yes, this is based on the Westfall paper. If you send me an Email at EJ.Wagenmakers@gmail.com I can give you the thesis of Tim de Jong who explains how it's done.
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Is this the fact that Age is recognized as a nominal variable? Of course the program should not crash but give an informative error message instead. For these and similar issues, our programming team can assist you more effectively if you post on ou…
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http://www.ejwagenmakers.com/2015/NuijtenEtAl2015.pdf
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Well the reliability of the estimates is indicated directly by the width of the posterior distribution. Your frequentist reviewer would have to explain why the evidence for this specific data set is less reliable than is indicated by your analysis. …
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Dear Stefan, Yes, this works. However, be sure to add the relevant references (in particular the work by Rouder and Morey). You might also mention that these are the settings of the BayesFactor package. Cheers, E.J.
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Hi Philip, Theoretically, it does not matter what your sample size is. With low samples sizes, the posterior distributions will not be very different from the prior distributions, because not much has been learned. Of course there may be specific p…
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I'll attend some other team members to this post E.J.
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I am not sure what goes wrong... I have tried this with 0.9.0.1 and the latest 0.9.1.0, and it works like a charm, for both the Bayesian as well as the classical analysis.
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Can you send the JASP file, perhaps only with the gender column?
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Also, you might want to check that the problem persists for the 0.9.1 version (out just now)