EJ
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- EJ
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Comments
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Hi Laura, JASP uses lavaan code, so it would just be a matter of writing the required lavaan syntax and pasting that into the SEM window. Cheers, E.J.
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Hi Ravi, A covariate is something continuous, like GDP; a factor refers to a discrete category, like country. Sometimes there are no covariates or factors of interest, so it is purely optional. Most people would recommend a random effects model; how…
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That's strange. I'll notify the team, but this is really more appropriate for our GitHub page (https://jasp-stats.org/2018/03/29/request-feature-report-bug-jasp/) E.J.
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Hi Emma, Some general remarks: Missing data is not a problem for the Bayesian model (at least not in principle) You probably want to use a crossed-random effects model instead of ANOVA? In this case you should use our mixed model functionality (unfo…
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In order to help I think it would be good to see some more background -- maybe a screenshot of the data, and a more precise description of what it means for JASP "not to like zero's". It is also not clear to me why you would model this as …
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I don't see why it would be problematic to add interaction terms. JASP uses lavaan, so I recommend you consult the lavaan documentation (or Google the right key words). E.J.
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When you have activated the mediation analysis in JASP and you click on the blue "i", the help file will appear. At the end of that file, there are two papers referenced. The most conceptual one seems to be this: Jeremy C. Biesanz, Carl F.…
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Hi Mariamr, Yes, I think that two separate ANOVAs are an acceptable alternative solution. Cheers, E.J.
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A BF is like the scales of Lady Justice -- when one scale goes up the other one must go down; they are in a one-to-one correspondence. So if you have BF10 = 5 the data are 5 times more likely under H1 than under H0, and this is evidence for H1. This…
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You could generate a column with random binary numbers. Then you could use that to filter one subset or the other. E.J.
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Thanks for reporting this bug -- it would be great if you could post it on GitHub so the programmers can see it and take action! Cheers, E.J.
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Hi Markus, I'll ask the other team members, but I think it is cleanest if you create new columns or new files for each filter setting. Cheers, E.J.
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Dear ladonnalr, We get this question more often. A screen reader cannot be used with JASP effectively at the moment. Key-navigation is present but not fully implemented. So it would be hard to navigate even if the screen reader works. We are very mu…
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The default setting for the Bayesian correlation is a prior width of 1. This is based on a stretched beta distribution that is symmetric around 0.5, so beta(a,a). The prior width is then defined as 1/a. It is clear that "a" should be highe…
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Hmm I think you might want to do this many times, and that would be easiest to achieve in R. In JASP, if you just want to do this once, I guess you can create a new column with random 0 and 1's, then use that to filter either one subset or the other…
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I do see it mentioned in https://en.wikipedia.org/wiki/Effect_size#Cohen's_d You take the (pooled) SD and divide by sqrt(n) (or a pooled version in case of the unpaired, unequal N case) E.J.
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Well I believe there is some discussion on using the F-test for equality of variance, because it is rather sensitive to the assumption of normality. Anyway, we do have tests for equality of two variances as well. Best to check out the program and is…
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How you calculate SE depends on your effect size measure (Cohen's d, log odds ratio, etc). For any particular measure of interest, I believe the Wiki entry generally shows how to compute the SE. E.J.
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For an intuitive interpretation see also the text above Eq 8 in this paper: https://www.tandfonline.com/doi/full/10.1080/02664763.2019.1709053 E.J.
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Hi Maria, Your BF10uncorrected = 0.173, meaning that the data are 1/0.173 = 5.78 times more likely under H0 than under H1. In other words, BF01uncorrected = 5.78, meaning you have evidence in favor of H0. The multiplicity correction increases that e…
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Hello may01dz, Yes, as used by ANOVAs for instance. Cheers, E.J.
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exactly E.J.
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Hi Manuel, Hmm yes. This should not be too difficult I think, but it has not been done to the best of my knowledge. The thing is that the simple main effects use the information of some of the other cells in the design (this is the benefit over t-te…
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I'll ask, but the help file does mention the emmeans package, so that would support the conjecture from MSB. E.J.
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Hi Giovanni, I assume it is just the standard method, as mentioned for instance at https://en.wikipedia.org/wiki/Student%27s_t-test Also note this post that point to a relevant document: https://jasp-stats.org/2021/02/03/the-jasp-verification-projec…
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Hi Mila, Hmm. Well if it can be coded in lavaan then it will work. I'll ask our expert. Cheers, E.J.
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The test is similar to ANOVA in the sense that it compares the H0 of "the groups are equal" to the H1 of "the groups are different". If only one group is different (but clearly so) then H0 will fair poorly compared to H1. Yes, va…
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Hi Mirna, I took a look at your JASP file and it seems fine. I am not sure what that message about the proportion test means, but I will look into it. For more examples and background information see https://link.springer.com/article/10.3758/s13428-…
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Hi Mirna, Sorry for the tardy response. I will take a look at your JASP file soon. Well the prior concentration determines how close the prior distribution is with respect to the point of equal proportions. For instance, For instance, if we have a 2…
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Yes we are revamping the functionality so we hope to have this sorted out in the next version. Cheers, E.J.