EJ
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If you are interested in the interaction, you can also compare the 2-main effect model against the full model. With few models you don't always need the inclusion BF. Cheers, E.J.
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Dear August, The ANOVA as borrowed from the BayesFactor package is really a linear mixed model. But in general, the same assumptions apply as they do for the frequentist version. Yes, the Bayesian approach generally allows all sorts of more flexible…
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What needs to be normal is the distribution of variances across subjects, right? I don't see why that wouldn't be (approximately) normal. In your RM ANOVA, I am not sure how your ultimate test involves the variance across the x,y,z. The interaction …
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Hi Richard, So far, as you indicate, JASP has focused mostly on the *evidence*, that is, the relative predictive performance for two competing hypotheses (aka the Bayes factor). The reason that we have not put in prior for the hypotheses is that the…
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I have attended the relevant JASP team members to this forum entry...
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I've passed this on...
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Yes. Depends how principled you are about the principle of marginality, I guess :-) E.J.
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Ah I see. Well but then you can simple compute the sample variance per subject and t-test this between the groups? Of course this ignores the uncertainty about the sample variance, but that would be the approach that people are often using currently…
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I'll attend him to your post
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This particular analysis includes a numerical routine. This means that unless you take an infinite number of samples (which takes an infinite amount of time) the results will change a little bit from one run to the next. The extent to which the resu…
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Yes, it's an issue of numerical precision. Apparently the posterior mass of the models *excluding* that main effect sums to epsilon, with epsilon so close to zero that the number cannot be represented on your computer. E.J.
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For an intuitive idea of when a Bayes factor is compelling see https://www.bayesianspectacles.org/lets-poke-a-pizza-a-new-cartoon-to-explain-the-strength-of-evidence-in-a-bayes-factor/ Cheers, E.J.
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Hi perdavidson, Sorry for the tardy response. Going by the main output table, the null seems to get most support from the data. The "only-Emo" model and "only-Villkor" models also get some support, but a factor of 4 to 5 less. Al…
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Sorry for the tardy response. We are very close to a new version (a week from now) and I hope this solves your problem. But, in general, for bug reports and feature requests we hope you can use our GitHub page -- this way the problem is accessible t…
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Hmm this is interesting, I'll pass this on. Cheers, E.J.
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Hi Adam, No I don't think that this is valid in general, although I would not be surprised if it is a fairly good approximation under many circumstances. This would be an interesting topic for a statistical study. Well you'd need an interval or SE…
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Dear Hongxia, This is briefly described here (for the case of ANOVA): https://link.springer.com/content/pdf/10.3758%2Fs13423-017-1323-7.pdf We have almost finished a paper explaining these concepts for regression in more detail. Furthermore: We have…
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Hi HMStat, To facilitate the discussion it would be great it you could show a screenshot. We are working on ANOVA help files for the next release, so this may come in handy. Cheers, E.J.
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Yes, that could work. The next version of JASP will have posterior distributions for the ANOVA/ANCOVA. Cheers, E.J.
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:-) The real thing is a direct comparison of variances. We have something really cool under development here (there will be a blog post and a preprint once it's done), but there is also recent work in the Tilburg lab of Joris Mulder. This is not in …
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Hi Vanessa, There may be people out here to assist with this general stats question, but doing so is not really the purpose of this forum. However, there is some good news too: in order to assist you with questions such as these, we are setting up a…
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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 …