EJ
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- EJ
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Dear Alablanchet, This is a good candidate for our GitHub page (for details see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/). I believe we are already aware of this problem and it's fixed in the upcoming release. Cheers, E.J.
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Hi Chris, The computation of these quantities requires a numerical procedure, and this comes with (very small) additional fluctuation. Cheers, E.J.
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Hi Darren, I'll pass this on to Johnny, but just to be sure: are you asking about the frequentist or the Bayesian implementation? Cheers, E.J.
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Maybe that is a good approximation (in some circumstances...haven't checked it out) but it's not the real thing (i.e., computing a ratio of marginal likelihoods), and we need the real thing to check whether and under what circumstances the approxima…
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Hi Caroline, Basically, there are two default ways to set the prior model probabilities. One is uniform (basically assuming that every predictor has probability 0.5 of being included; this does lead to a prior preference for models with 50% of the p…
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Yes, that's right Cheers, E.J.
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Dear Narcilili, You can't get this from JASP yet (other than by eye-balling the posterior distributions), but it's on our list. Cheers, E.J.
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Hi Eric, Two quick remarks: Since BFs are defined as ratios, averaging them is problematic. For instance, assume data set 1 gives BF10 = 3, and data set 2 gives BF10 = 1/3. Overall, the data are nondiagnostic, but averaging 3 and 1/3 does not give 1…
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Hi Gareth, Yes, these are equivalent My own preference is to keep the exploratory and confirmatory stage separate. So I would encourage exploratory analyses, but the confirmatory stage should feature new data, and not contain old data that inspired …
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Hi Peter Yes, they are the same, because for this more descriptive measure we assumed a uniform prior. And in this model, the results will then be identical. Cheers, E.J.
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Yes. So then you need a column that codes the condition (A, B, or C) so that you can do "split" by condition. The data file would look like this: part.nr. DV condition 1 350 A 1 450 B 1 …
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This is strange. I'll bring this to the attention of the team. BTW, for future bug reports, you are invited to post them 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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And you want box plots for every repetition, right? So then you need a column that lists the that information. For instance: repetition RT 1 550 1 645 2 440 etc Then you do "…
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Let me check, but I think you only get them in a single plot if you have all values in a single column and then use the "split by" option (that points to another column that indicates the variables) E.J.
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Not yet, but Johnny is working on it We do have a Bayesian version of Kendall's tau in there (which I personally find more elegant than Spearman) E.J.
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I think this has been fixed for the upcoming new release. Let me check...
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Hi Mila, What I would do is first add your control variables to the null model, and then compare this null model to the model with the other variables added. This can be done in different ways (compare to the model with all variables of interest add…
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This suggests some actual statistical research; we'll look into it E.J.
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Hi Aaron, Sorry about the long delay. This is similar to the analysis for the "Bugs" data set, discussed for instance in the Part II paper here: https://link.springer.com/article/10.3758/s13423-017-1323-7 I cannot see a gif/YouTube video o…
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Dear Clement Sorry for the tardy reply. In general, you can obtain evidence for any two models using transitivity, the way you outlined. But there are two crucial steps, one that comes before and one that comes after: The step before: which models d…
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Since your code is based on the BayesFactor package, and Richard knows more about change scores than I do, I've forwarded your question to him (sorry for the tardy response, just had kid #2, makes it difficult to keep up) E.J.
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Dear Kimberly, Sorry for the tardy reply. Looking at the analysis of effects, the data *increase* the prior inclusion probability from 0.263 to 0.750, for an inclusion BF of 3.8; this is mild evidence in favor of Factor 2. So that's not exactly what…
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Dear Gabriel, Thanks for bringing this to our attention. We will look into it and keep you posted! Cheers, E.J.
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Easiest: "default prior used by the BayesFactor package (details, ref), as implemented in JASP" Cheers, E.J.
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Dear C, Thanks for the post. This seems like a feature request/bug report issue. It would be great if you could post this issue on our GitHub page (for details see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/). It's the most ef…
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Hi winwinwin, The implementation of the Bayesian ANOVA was lagging a little bit behind. The upcoming version will fix this! (courtesy of Don van den Bergh) Cheers, E.J.
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Dear cludowici, This is a tricky one for me to answer, as I am mostly working with JASP, and Richard has reservations to model-averaging. But I'll sign him in nonetheless, maybe he can at least speak to the general setup of the analysis. Cheers, E.…
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Hi Ronen, This is a really interesting issue. I think you should also be uncomfortable with the frequentist results, probably. But what seems to be going on here is model misspecification, on more than one level (the sphericity and the random effect…
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I'll ask the expert, Erik-Jan! (yes, almost the same first name)
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Dear Uhandoko, There is a whole literature on how to predict exactly. In general, I would say you want the uncertainty surrounding your point prediction, so you'd want to take the distributions for the beta's into account (rather than just focusing …