EJ
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- EJ
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Comments
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Hi Cristianne, I've attended our expert to this. Because of the holidays it may take a while before you receive a response. Cheers, E.J.
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This is really strange. I have tried to reproduce this but no luck so far. Is this a data set from the JASP data library? Also, this is clearly an issue for our GitHub page instead of the Forum (for details see https://jasp-stats.org/2018/03/29/requ…
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Yes, you can email info@jasp-stats.org
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I don't think so. Have you searched online, possibly on YouTube? E.J.
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The JASP team does provide training, but usually to entire groups or teams. What are you looking for exactly? (number of hours, skills you wish to acquire, background knowledge you have etc.) EJ
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Yes, GitHub is dedicated to feature requests and bug reports, whereas this forum is meant for more high-level statistical questions and discussions. EJ
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Also, I found the issue and added the information you provided: https://github.com/jasp-stats/jasp-issues/issues/1330
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This issue is very much on our radar -- in fact I believe it is currently being worked on. If you go to our GitHub page you should be able to find this issue, and you can indicate you value its implementation. EJ
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In the past we've had major updates about three times a year. We are making some fundamental changes to make this process easier (so that we can update individual modules immediately without having to go through an entire release cycle). EJ
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I am still looking in to these sorts of problems, with an eye to application of the 3p*sqrt(n) rule (https://osf.io/preprints/psyarxiv/egydq). EJ
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This does not strike me as unreasonably large EJ
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If there is no hard error, this can be tricky to diagnose, in any program.
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I've asked our expert
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A paper on how to go from AIC or BIC to model weights: Wagenmakers, E.-J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic Bulletin & Review, 11, 192-196. https://www.ejwagenmakers.com/2004/aic.pdf
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I do not immediately see how the problems with WAIC and LOO would imply problems with BIC. The BIC might be "unreliable" if the MLE is borderline identified. EJ
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Yes, but there is another possibility. It may be that the data provide evidence for a "pure" interaction -- so there is only the interaction, and no main effects. This violates the "principle of marginality" which states that if …
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@Michael_Jasper : yes you can multiply but it needs to be clear what hypotheses you are comparing. @andersony3k: Consider four factories, each of whom creates four products: X, Y, M, Z. The factories create these products in different ways. In Facto…
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Hi Marissa, Sorry about the tardy reply. I will make some inquiries Cheers, E.J.
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Sorry for the tardy response. It is important to check that your covariate does not overlap (substatially) with PTSD severity, or you will be removing the very thing you are interested in. As far as the results go, the null model predicts the data b…
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Could you provide the data? (or fake data with the same structure?) EJ
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This seems a reasonable explanation. Difficult to say more without the data and screenshots. EJ
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I don't think there is, at the moment. There may be, but it will probably involve some effort to get it to work. EJ
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Yes you can conduct those two test, but when you want to combine them then it would be prudent to add those other hypotheses. Of course you can add the negative correlations as well, expanding the hypothesis space. I had hoped you have some substant…
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I suspect that some cell entries are empty. If they are not, this is a bug, and you can post the issue on our GitHub page, which will bring you in direct contact with the programming team (for details see https://jasp-stats.org/2018/03/29/request-fe…
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Well, I would still like to argue in favor of the 4 hypotheses I outlined above. And these hypotheses might just be associated to particular people/forecasters: John's believes that XY>0 and MZ >0 Mary believes that XY>0 and MZ=0 Amy belie…
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Good point! It may be argued that there are at least four hypotheses: XY>0 and MZ >0 XY>0 and MZ=0 XY=0 and MZ>0 XY=0 and MZ=0
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More precisely: if the size of the correlation between x and z under H1 affects the knowledge about the size of the correlation between z and m under H1, then independence is breached EJ
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You can multiply the BFs if knowledge of the result for x and y would not alter your knowledge for the correlation between z and m. Now you know that x and z are highly correlated, but I don't think this is relevant for the correlation between z and…
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This is not the same issue I don't think. Did you post yours?
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Hi Dan, I am not 100% sure what you did, but the BF is based on relative predictive performance for observed data y. It so happens that the t-value and sample size is a sufficient summary of the data, so that no information is lost when you enter t …