EJ
About
- Username
- EJ
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Comments
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:-) Yes, when in doubt about what the subscripts mean, I always look at the change from prior to posterior model probability. That shows massive evidence in favor of H1, in line with the classical result. E.J.
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I've forwarded this to our experts E.J.
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I've forwarded this to our experts E.J.
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Dear Maria, I'm sorry to hear this. When you have questions like these it is best to involve the JASP programmers. You can reach them by posting the issue on our GitHub page (for details see https://jasp-stats.org/2018/03/29/request-feature-report-b…
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In general the weighting of cases (also helpful for survey work) needs to be implemented still. A poke on our GitHub page would be welcome. E.J.
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Let's say you get a BF10 = 3. Under equal prior probabilities, this means a posterior probability of 75% for H1 vs H0. In a simulation for what you can expect from a replication, you would first sample either H1 (with probability .75) or H0 (with pr…
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I suspect they are in alphabetical order. An ugly hack would be to call the conditions "Apost" and "Bpre"; if this plot them in the right order you can save the plot as a pdf and then edit out the A and B. (let us know whether th…
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(that being said, it seems to me that in order to assess collinearity a regression approach is the first thing I'd think of) EJ
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Hi Alejandro, Maybe you can be a bit more specific; perhaps including a mock data set and some screenshots would help... Cheers, E.J.
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Not yet, but the upcoming version (expected this month) will have a first implementation of this. E.J.
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That should be mentioned in the documentation. And you should be able to change this in the GUI...anyway, a check is to use a one-factor RM ANOVA with two levels and see whether you get the same result. E.J.
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Sorry to have missed this earlier. The post was repeated later and I've answered it there. E.J.
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Hi MikJ, Thanks for sticking around, and sorry I missed this. Will bring it to the attention of the group. Some quick comments: The table is probably easier to interpret if you put "best model on top". It may be even easier to interpret if…
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Hi Ravi, I don't think we have this yet, but I'll ask. Cheers, E.J.
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I'll pass this on to our experts Cheers, E.J.
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I'll ask our expert! Cheers, E.J.
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At the moment the Bayesian mixed model functionality does only parameter estimation, not null hypothesis testing Cheers, E.J.
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Hi Marijn, I'll ask our expert. This seems to be information that ought to be reported in the help file... Cheers, E.J.
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Hi MB, We took our inspiration from the Hastie & Tibshirani book. So I would basically consult a classic text (or watch some tutorial videos on YouTube) Cheers, E.J.
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This is really an issue for our GitHub page, but I'll direct out programmers here. My initial guess is that this is due to the admin settings. If you can't change these, what you can do is to download and unzip the pre-installed version of JASP. E.J.
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Dear num3, This is not trivial. I believe the Rouder et al. 2009 PBR paper provides some details, and so does the Gronau et al. 2020 American Statistician paper " Informed Bayesian t-tests." (available on my website). And then there are th…
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I'll pass this on to our experts E.J.
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Not right now, but it would be a good feature request for our GitHub page! E.J.
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Hi Max, Johnny van Doorn's work is relevant here (it is the basis of the implementation in JASP). The help file gives van Doorn, J., Ly, A., Marsman, M., & Wagenmakerss, E.-J. (2020). Bayesian rank-based hypothesis testing for the rank sum test,…
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We have worked hard on this, and I am happy to report that the next version of JASP will have R code integration. We hope to have a "nightly" (experimental version) with this functionality out any day now. For this particular version, the …
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Dear B_S, I suspect the computation of the CI interval for Spearman's rho requires the use of the bootstrap. Since the bootstrap is ticked off by default, no intervals are initially produced for Spearman's rho. It would be possible to have the boots…
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Thanks Quentin! E.J.
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With your sample size and design, I am not surprised that p=.041 maps on to BF01 = 10/6. I'll ask other team members about this and see what they say. Cheers, E.J.
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This is a rundimentary editor. Feel free to post suggestions for enhancement on our GirHub page. You can set the scale on each axis separately. E.J.
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That's great -- feel free to elaborate how you solved it, to help other users! I am sorry I did not get to address this issue straight away.