EJ
About
- Username
- EJ
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Comments
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We don't have generic bootstrapping functions, but I am sure they are there for the functions that require them (for instance, the machine learning module offers many such procedures). If you have an example where the bootstrap has advantages but we…
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This is under development. If you post it as a feature request on our GitHub page (or give an existing request a thumbs-up) it will up the priority. Cheers, E.J.
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Hi NinaJk, I'm not sure bootstrapping will help with model misspecification or small sample sizes -- the bootstrap was meant to obtain an estimate of sampling variability in cases where no analytic solution is available (which includes cases where t…
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I've attended Richard to your question! Cheers, E.J.
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It should work more easily with the R code I think... Anyway, you can string together the exclusions using the AND (^) operator: "ID not-equal-to 23" ^ "ID not-equal-to 9" etc. E.J.
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If you execute a paired-samples t-test and request the associated raincloud plot you'll see the changes for each unit indicated in the plot. Or am I missing something? Cheers, E.J.
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I've forwarded this issue, you should hear something soon E.J.
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Hi JASPLearner, I would take the best model as a point of departure. Comparisons to the null model are rarely informative. Cheers, E.J.
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I've addressed this in a different thread: basically, the data do not provide evidence for the full model over and above the two-main effects model. You can see this better when you select "compare to best model" or add the main effects to…
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Hi Rik, In the current Bayesian implementation it is problematic to add Group as a covariate; it is a factor, not a covariate. You can feed it as a covariate to the Bayesian linear regression setup, but only because JASP does not realize that Group …
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Dear JASPLearner, I would say that the data offer evidence against including the interaction. You may want to tick "compare to best model", or add the main effects to the null model in order to focus on the evidence for adding the interact…
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Dear Ajestudillo, 1 & 2: yes 3: yes, (I assume you refer to the 4.009); note that you can add the main effects as nuisance factors to the null model (under the "model" tab) so you get the comparison between the two-main-effects model a…
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Hi Neha, Yes, JASP offers Bayesian rank-based alternatives. They are under the regular t-test menus. The help file will point to the relevant references. Cheers, E.J.
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Hi Brunofd, What functionality in JASP are you referring to? The SEM module is based on lavaan. Do you have a data example that demonstrates the discrepancy? Cheers, E.J.
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Not yet, but you could issue a feature request on out GitHub page. You might want to explain why you want the Bayesian bootstrap though (in this case you can have MCMC samples from the posterior distribution). Cheers, E.J.
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Ah, so you want to filter just the one variable, but not automatically the others as well? I don't think you can do this now, but it would make a good feature request on our GitHub page. E.J.
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Michael has to concentrate on his studies for the moment but I'm going to find someone else to look at this... E.J.
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I'll attend Jill to this (but I would suggest consulting the literature as well) E.J.
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Hello Mani Currently JASP cannot handle multiple files at the same time. You could make a feature request but in the short term you are probably better off creating a new csv file with the data combined. Cheers, E.J.
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That's strange, the "i" icon does work for me. You could post the issue on our GitHub page -- I am not sure whether this is a problem for other people as well. This should be in the help file -- I'll forward this to our Network expert. Not…
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I am surprised to see that it is not. If you add it as a feature request on our GitHub page I'll give it some priority.
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a) Yes you can do this, especially when you use informed prior distributions. The null divides out so you are left with a direct comparison between two instantiations of H1. b) This is a little tricky in this specific case. I suggest that your quest…
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I've passed this on, we'll be in touch! E.J.
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Hi Matthew, I am not quite sure what you mean with "muting" -- do you mean filtering? Or are you using the dataMode/SKF version and are you in data editing mode? A screenshot would help! Cheers, E.J.
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Hello Tong, You might try and turn on "Safe Graphics" in the Preferences. Please let me know whether that worked. If this does not work, please post your issue on our GitHub page so the programmers can deal with it. The download page has a…
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Yes, I agree with eniseg2. Sorry about my tardiness, I am a little busy at the moment -- hope to be back up to speed soon. Cheers, E.J.
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Sounds like a great idea! We'll add you to our worldmap if you aren't already on there. Could you post this feature request on our GitHub page? (for details see https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/) I am sure we can inc…
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But you need Log(eyes + 1), right? So the log should go over "eyes+1"
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What is the log1eyes transformation? It is not log(1+eyes)...can you make a screenshot of the transformation rule you applied?
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Dear Haizeydays, Which values are infinite when you transform them? Do you have a screenshot? Cheers, E.J.