patc3
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Don't add paths from controls to IV, only to mediators and outcomes (here it fails because your IV is categorical). Age and mschool shouldn't predict NEGFAMDI (that's your IV right?)
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To make parameters appear in the "Parameters in model" you need to click ctrl+enter to apply the model you wrote. Yes it's possible in both JAGS and Process. Why do you prefer JAGS? Here's the setup using the Process module (1 predictor = …
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Equivalently you can also specify this using paths (no need for Hayes model numbers): https://forum.cogsci.nl/uploads/678/7Y4RKGPZRXHD.png
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Wow you're right, I hadn't realized Bayesian had been implemented in Process. Here's how I replicated the analysis: https://forum.cogsci.nl/uploads/767/IYWSNSLDQZBR.png https://forum.cogsci.nl/uploads/217/MA48FUTK55AS.png
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I don't think you can do it automatically through a menu, but you can do it through the JAGS module. Here's a syntax where x = Extraversion, m = Satisfaction, and y = ITL (intention to leave), i.e. extraversion leads to higher satisfaction which in …
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For a non-normal dependent variable, depending on the distribution of the variable you can also use generalized LMM. This is parametric, but it assumes the outcome follows some distribution other than normal (e.g. there's Poisson for counts, inverse…
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Also I forgot to mention, the reason you center in a moderation analysis is that the interpretation of the "simple effects" in the output (i.e. the effect of each variable, e.g. x1 and x2) is the effect of that variable when the other vari…
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Hi Seth, 1) "I was curious if anyone knows why JASP uses z-tests by default for this and whether there is any way to change it to t-tests": the reason is that the module uses the R library lavaan, which is a general-purpose structural equ…
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@Yuichiro it's not possible from your screenshots to see what the problem is. I also don't understand what the problem is from the textual description you gave.
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What's the problem with the screenshot you showed?
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You're welcome for the help Per 🙃 Did you try to change the values when it's a nominal variable, or change the labels when it's a numeric variable? Either way you can get the text you want. You can try both too and see which one you like best/works …
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It looks like you can't change labels for a nominal variable (where the value itself can act as a label, since text is allowed). If you want a numeric value (which you can use in analyses) with labels, you can change the variable type to scale (curr…
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https://forum.cogsci.nl/uploads/055/I66SXS5QIDDQ.png
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From memory I think it's called variance covariance of effects or something like that (right above the checkbox you checked to get individual random effects)
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By default JASP estimates all possible random effects (including those for interactions). You have to go under Model and remove (uncheck) random effects (in your case, you only have a random intercept, so only intercept should be checked): https://f…
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sorry I'm not sure what the answer to your question is, so I'll let others chime in
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Michael, I think there might be some confusion as to what problem GVIF solves. GVIF is designed to accommodate categorical **predictors**, whereas VIF had been originally designed to accommodate numerical predictors only. As far as I know this as no…
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https://forum.cogsci.nl/uploads/987/R03GP0H44MY4.png
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Insert new column using R code called AtLeast26: as.numeric(Age >= 26)
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Could the numeric stats use numeric values and frequency tables use labels? (E.g. value 1 has label 3). Just a guess, I'm on my phone
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you can drag and drop from one line to another: https://i.imgur.com/u2rcX3H.gif
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If you're using constructor (drag-and-drop) column, "and" is ^, so you should read ColA>25 ^ ColB>25: https://forum.cogsci.nl/uploads/076/8Z3FBGAQ74CS.png If you're using R code, "and" is &, so you should read ColA>…
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I also can't get it to work😭😭😭
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That's because your variables are set as ordinal rather than scale, you can change this in the data panel (leftmost panel) by clicking the variables' icon: https://forum.cogsci.nl/uploads/401/YILILSA1C6RZ.png
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random intercept
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it's like JASP is taking the approach of model pruning rather than model building, but it rarely runs out of the box because of this, and not everyone is savvy enough to know what the error means...
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I would do random intercept personally it's bad because it rarely runs (e.g. if you reproduce the example in the data library from scratch by going into mixed -> linear, it throws an error until you remove all random effects but the intercept, as…
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my guess is that you need to look at Model -> Random effects: https://forum.cogsci.nl/uploads/129/3Y0MAU60OFZC.png By default JASP has the very bad default behavior of adding all possible random effects, whereas you specify those manually in SPSS…
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I mean, it definitely exists in SPSS... https://forum.cogsci.nl/uploads/990/5MG6DHVECI4C.png That said @tahidus , perhaps this page (or something similar) could help: https://libguides.library.kent.edu/SPSS/Multiple-Response-Sets I didn't read it al…
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yes, do an EFA and specify 1 factor https://forum.cogsci.nl/uploads/954/OYXMZIN1F7D2.png https://forum.cogsci.nl/uploads/516/IMRGDSTHB428.png