EJ
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 EJ
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Hmm I noticed I basically reentered my earlier answer. Well, goes to show I didn't change my mind about this. E.J.

Hi NvH, Yes, this has been argued, mostly by subjective Bayesians such as Lindley. The Bayesian "correction" for multiplicity is in the prior model probability. If you are testing 10 effects, do you really believe that every single test is plausi…

Hi Franziska, That is the same thing, isn't it? The shape of the boxplot is a little different, but the information appears to be identical (?) Cheers, E.J.

Hi Ondrej, Great question. Ideally, you'd integrate the ANOVA structure with the model underneath. When that is difficult some twostep method could be used. Here's a paper that may be relevant: https://www.collabra.org/article/10.1525/collabra.7…

Good question! The .707 from the default test is really 1/2 * sqrt(2). What you can do to check is use the informed test with "0.7071068" instead  the result should be closer. Also, we have a better routine for the informed ttest now (much faster…

Yes, this should be resolved. You can set the preference for the number of decimal points in Preferences. See attached screenshot. Cheers, E.J.

Hi Philip, The %error gives an indication of how accurately the numerical methods have estimated the BF. I think that it's the standard error expressed as a proportion of the BF, but the BayesFactor package should explain what it is exactly. When…

Dear Michif, I'll ask Johnny to clarify this. We probably call an existing R package. Cheers, E.J.

* If you set BF to "BF01" instead of "BF10", then you'll see how many more times the best model predicted the data (numbers > 1 are usually easier to interpret). * The most popular way to test an interaction is to compare A+B to A+B+A*B. The eas…

Hi Patrick Yes, the copypaste functionality can be improved. The default copypaste for tables copies the html code, but I don't think that this is ideal. We also have "copy as" and then offer LaTeX code, but I hope we can add ASCII in the futur…

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://jaspstats.org/2018/03/29/requestfeaturereportbugjasp/) 2. A new version…

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, but n…

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.

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…

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 reprogram all of our figures, and that's just the start). Cheers, E.J.

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 …

yeah, taking that interrelationship into account would be best but I am not sure it is worth the trouble E.J.

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 the ana…

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…

Hmm. It seems that you can use three separate rankbased correlations between questionnaire score and number of fixations?

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 = …

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 unde…

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 test by adding time as a co…

Great question (and sorry for the tardy reply). We are currently working on this! It is not in JASP yet. Cheers, E.J.

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 twoside…

I looked at GitHub and see that you are now in conversation with the team. Hope this is resolved quickly. E.J.

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…

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://jaspstats.org/jaspmaterials/ and then https://osf.io/ahhdr/ Cheers, E.J.

Yes, that's fine. But the effect is not small! So I would push back here. You have a medium effect size with a mediumtolarge sample size. The result of that combination is displayed in the priorposterior plot. Clearly an effect size of 0 is not s…

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://jaspstats.org/2018/03/29/requestfeaturereportbugjasp/). Cheers, E.J.