EJ
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- EJ
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Hi AnaOnar, Hope this helps: https://psyarxiv.com/spreb See also https://link.springer.com/article/10.3758/s13423-017-1323-7 and https://link.springer.com/article/10.3758/s13423-017-1343-3 for more general introductions. Cheers, E.J.
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Hi Ben, I'll forward this to our SEM team member (who is on vacation right now). Thanks for reporting this. Cheers, E.J.
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Ah this is very interesting. I'll forward this to the team member tasked with this project! E.J.
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Hi August Because it's descriptives, and not inference, we use the credible intervals with uniform priors on the entire real line (so basically a confidence interval). I've always been uneasy with this; maybe it would be best to leave the user the o…
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Dear August, Thanks for posting the issue and sorry for the tardy reply. About the effect size question: I do think we have recently added posterior distributions in JASP, but I am not sure they are for traditional effect size measures. I'll ask the…
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Hi JPZ, Sorry for the tardy reply. I am not sure what we offer now (I think the weighting is there for some analyses, but not all). Could you propose some books or R packages so that we have a more concrete handle on what is needed? It would be grea…
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Dear AMa, Sorry for the super-tardy response. I've forwarded your issue to the team. I think this particular interaction term was still under development, but perhaps Johnny has recently added it...we'll let you know soon Cheers, E.J.
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Actually, we also offer color palettes for the color blind, and we have keyboard shortcuts for most of our navigation tasks. We will make a list of what we do now and add it to the FAQ on our website. E.J.
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Dear Andersony3k, Thanks for bringing this to our attention. We have discussed this with several people already, and are considering how to make the necessary changes. Right now, the only thing that JASP allows is to increase and decrease the font s…
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Hi Tom, Yes, we hope to add this functionality soon. The implementation will be along the same lines as linear regression, so we will also be using Merlise Clyde's BAS package from R. Highly recommended. Cheers, E.J.
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Yes, both in classical and in Bayesian form. The work is done (!), but I am not sure whether it will be in the upcoming release (which we are going to test now) or the one after that. In the mean time, if you want to run the frequentist test (which …
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Hi mcp, Sorry for the tardy reply. In JASP, when you select "independent samples t-test" you will be offered the option of doing the Mann-Whitney, so indeed, that's the one you need. This may also explain the error you got when you were tr…
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Yes, indeed, this is not possible at the moment! I'll give it a bump on the GitHub page (which is the most efficient method; you can do this too -- https://jasp-stats.org/how-to-use-jasp/) Cheers, E.J.
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Hi H_S, Under https://jasp-stats.org/how-to-use-jasp/ you can go to Repeated Measures ANOVA, and view a YouTube video that will walk you through the basics. Cheers, E.J.
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I'll forward this to the team, but the purpose of ML is usually not to estimate parameters; the focus is squarely on visualization and prediction. Cheers, E.J.
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Maybe I misunderstand, but if you enter the main effect as nuisance parameters (included in the null model) then the BF for the interactions will be outputted by JASP directly. Cheers, E.J.
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Hi eniseg2, The problem of multicollinearity is a hard one. From looking at the individual models you can assess whether it is the case that high-probability models either include the one predictor, or the other, but not both. Of course the investig…
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Hi Wim, I've forwarded this to the team. As an aside, for issues like this (where you suspect there is a bug) you will be helped more efficiently if you post it on our GitHub page (for details see https://jasp-stats.org/2018/03/29/request-feature-re…
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Hi Alexa, The correlation with the default (uniform) parameter prior under H1: I have no problems with it, and it is what Jeffreys proposed. But you might try to make H1 directional (you probably have a direction in mind? either a positive or a nega…
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Hi Ellen, Hf = full model (with interaction); Hm = main effects only model; H0 = null model BFf0 = 1.475; BFm0 = 5.058 BFf0 * BF0m = BFfm, or BFf0 / BFm0 = BFfm, meaning 1.475 / 5.058 = BFfm = 0.29, so data are about 1/0.29 = 3.45 times more likely…
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Strange. This is really a topic for our GitHub page, but I'll attend the team to this post. Cheers, E.J.
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If you'd like some twitter credits you can send your complete name or twitter handle -- otherwise you'll be acknowledged be Maurizio. BTW, do you have this as a gif? (this is the format we generally use)
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Hi Maurizio, are you OK if we add this video to our website and point to it on Twitter? E.J.
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Hi Mila, I don't think (1) is an option, and I'm not sure about (2). There are some Bayesian network models you could check out. I believe there is some recent work by Joris Mulder (Tilburg Uni) that may be relevant here. Cheers, E.J.
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Hi Nancysara_123, Please let us know on our GitHub page what meta-analysis features you'd like JASP to have! We aim to make students and researchers less dependent on commercial software. (for details see https://jasp-stats.org/2018/03/29/request-fe…
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Dear Tali, A similar question on this forum was answered by Dr.Mark, as follows: "Hi Stat_b The default output for linear regression is Model summary ANOVA Coefficients - with the intercept and unstandardised B values Mark"
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OK, that's informative, I'll forward your post. E.J.
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Actually, before I call in outside help, did you inspect these resources? https://jasp-stats.org/2018/06/27/how-to-filter-your-data-in-jasp/ and the gifs listed under https://jasp-stats.org/how-to-use-jasp/ E.J.
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I'll forward your post to those in the know. E.J.
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Hi Leonie, This is a good example of why it is not universally true that an interaction is tested by comparing the main effects model to the full model. The entire pattern of results across all models is important. I would present the entire table a…