EJ
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My advice: 1. Have an online appendix in which you present the annotated JASP output (and/or put the annotated .jasp file on the OSF). 2. In the main text, for ANOVA, use "best model on top" and describe the column of BF01s (this is genera…
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Hi Jonas, With the BF in hand (say 3 in favor of the null), you need to determine your own prior model odds (say 3 in favor of the alternative). Multiplying these numbers yield the posterior odds (in this case, 3 * 1/3 = 1). Then you can transform …
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Ah, so with the SD's weighted by N-1 instead of N (https://stats.stackexchange.com/questions/66956/whats-the-difference-between-hedges-g-and-cohens-d)? I think that this kind of bias-correction is a frequentist concern, as least as far as inference…
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I'll post this on the GutHub page. E.J.
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Hi Alon, This is more the expertise of Richard Morey, so I'll attend him to this, as well as Quentin Gronau. For what it is worth, I think you are right. The Bayesian ANOVA in JASP is really a Bayesian linear mixed model. Perhaps there is a post on…
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Hi G, A few remarks: 1. The sequential plot stays at BF=1 until about the 10th participant. I assume the first 10 were all from the same condition? Might be good to state explicitly (JASP assumes the participant came in in the order of the rows). 2…
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We'll clarify this in the table heading for the next release; I've made it an issue on our GitHub page.
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U stands for "uncorrected", so it does not include the post-hoc correction term that comes from the prior model probability.
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Thanks for not letting this go. I'll Email the student to request an update. Cheers, E.J.
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Dear xxPolyG, Yes, filtering is a common chore and although you can double-click the data and do your filtering in, say, Calc or Excel, this is somewhat tedious. So we are definitely going to add filtering capacity to JASP. When exactly this will h…
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Hi MMA, Well, the posterior distribution is not exactly a Gaussian (it is close, but for low-N it will have thicker tails). But from the median (=the mean if the distribution is Gaussian) and the 95% CI you can compute the SD. Cheers, E.J.
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Hi Larry, 1. Yes, the priors are all on delta, the standardized effect size (and sd indicates the uncertainty) 2. We are in the process of eliciting a number of other informed prior distributions. 3. For medium-large and large: interesting question…
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Dear MMA, What you are looking for is a "replication Bayes factor" (Verhagen & Wagenmakers, 2014) -- in other words, the change in evidence brought about by the data from the replication, having updated the prior distribution based on…
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From a Sacha Email: "The module doesn't recognize ordered variables yet." We will work on this as soon as Sacha returns from his vacation. It should not be too difficult. Cheers, E.J.
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Hi Lucas, I will take this up with our Lavaan expert, Sacha Epskamp! Cheers, E.J.
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Hi Shuang, Maybe the term "nuisance" is confusing. In the next version of JASP, we are replacing it with "include in null model" or something similar. The question when to do this is a substantive one, and the considerations are…
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Hi Ivan, Yes, you are right, it's 1.543. The choice of whether or not to look at the other effects depends on theoretical considerations I guess. The BF of 2.7 is obtained by comparing prior odds to posterior odds, so this includes the other models…
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Hi jjarryjasp, In later versions, we entered the text "dependent" on the y-axis. However, that is clearly not much better. The upcoming version should have the name of the actual dependent variable there (something you can adjust by editi…
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Hi Scott, For the t-tests, JASP now has "informed priors" that allow great flexibility in their specification. In particular, they can be centered away from zero (https://arxiv.org/abs/1704.02479). We are working to make the ANOVA and ANCO…
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We should include that information in a footnote. The "U" stands for "uncorrected", so it is the BF from a t-test on the two pertinent conditions. Cheers, E.J.
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The BF inclusion averages across all models under consideration. It looks at all models that include the factor of interest, and pits them against all models that exclude that factor. You then look at the change from prior inclusion odds (summed pri…
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Hi Nicolas, Not 100% sure, but these high BFs translate into very small probabilities, where rounding can make a big difference. To check, you could take an example where the BFs are modest. E.J.
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Hi Shuang, Well, statistically this is a tricky issue. I personally do not like the term "controlling for", because it suggests something that is impossible without an experimental setup. But in general, yes, you can do a "hierarchic…
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No idea! Can you attend us to this problem again please (on GitHub)? It would be good to sort this out E.J.
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Hi Nicolas, Sure, happy to oblige. I'll ask Tim to send the relevant code, or post it here. Cheers, E.J.
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I'll Email the student now. We discussed this issue yesterday in the JASP team. It would also help if you made this an issue in GitHub, if you haven't done so already. Cheers, E.J.
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Hi Ivan, Well, I am not so sure there is a big conflict. The BF for including the interaction is about 2.7, right? And the p value for your last analysis is about .01. That discrepancy is a little larger than what I usually see, but then again, thi…
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Hi Hannah, I assume you are talking about the t-test. Delta is the population version of the sample Cohen's d. So it is just the mean population difference divided by the population sd. You can find a detailed description in http://www.ejwagenmakers…
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Hi NT, Yes, mediation, moderation, moderated mediation, mediated moderation (if these exist): they will be implemented. If you want to urge the team to assign more priority to this development, please post a message on our GitHub page. Cheers, E.J.
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Hi Sarah, This occurs because that particular analysis requires numerical techniques. I am on my cell phone but I believe that under Advanced Optiobs you can increase the number of draws that determine the accuracy of the approximation. You could a…