patc3
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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
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Dmartin427 has a nice way to get it done. Steps 5-6 can be condensed into one step by using the function zScores(y) on the right of the screen nstead of manually dividing by the standard deviation of rawresiduals. Also if you insert column using R c…
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the difference between -29.402 and -24.435 is still very large no?
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there are three elements to fill: a condition value if condition is true value if condition is false otherwise you're gonna have to give more details about what you're trying to achieve
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@TarandeepKang your explanation was very useful
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This is likely due to having a dependent variable with a very large scale (e.g. salary in dollar amounts, or something even bigger). You could try to go in preferences and uncheck this box: https://forum.cogsci.nl/uploads/575/U9UJICY4DDRJ.png
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See GitHub issue here: https://github.com/jasp-stats/jasp-issues/issues/2926
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Thanks I remember now. I used to know how to get to multinomial regression, but it's so weirdly located that I couldn't find it anymore. Welp you're definitely right the UI is completely unresponsible to changes in the diagnostics section. It might …
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I thought JASP didn't have multinomial logistic regression? Am I misremembering?
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After you've followed EJ's suggestions, if you need to, you can revert back to a previous JASP version until a fix is deployed: https://jasp-stats.org/previous-versions/
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Nice! readxl::read_excel() works extremely well
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Where can we access the data? I wanna see for myself.. Or perhaps you can show your JASP input? To rule out user error (as I don't think the book got it wrong, and I would find it unfortunate if JASP was wrong)
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What if you change model test in the SEM analysis (see the second screenshot)? Also what if you pick mimic/emulate Mplus?
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That said, there's probably a couple of ways to get the t test: 1) create a new variable with two values and missing if not in either of the two conditions of interest 2) do an ANOVA with post hoc pairwise comparisons, though you might be forced to …
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Hmmm interesting... This looks like a bug to me
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CFA: https://forum.cogsci.nl/uploads/463/CITETK1B9CRF.png SEM: https://forum.cogsci.nl/uploads/925/READPHIC8Y8C.png
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Sorry no I don't know. What I do in that situation is I either use the default, or I use the default of a software that a lot of people use in my field (SPSS).
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Duplicate the analysis by clicking the green button and do it through separate analyses instead. My guess is it's a "lack of functionality", as there are some scenarios where you want the constraints to be the same across models; this is …
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There's several methods for calculating percentiles, and the SPSS and R defaults are not the same. (JASP uses R in the background) https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/quantile SPSS uses type 6, the default in R is ty…
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Of course the difference in residuals is due to the difference between the models, i.e. the addition of baseline as a numeric predictor. Baseline as a predictor uses up 1 degree of freedom, and if it interacts with another predictor, it uses up anot…
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What's your model? What's your lavaan syntax? Your question would benefit from a lot more detail... Personally I'm not sure what you're trying to achieve
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just means that they did group2 minus group1 and you did group1 minus group2. This is inconsequential. Same p-value, same conclusion, same difference being tested, etc.
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It's in ANOVA under Nonparametrics: https://forum.cogsci.nl/uploads/567/GLTZ3GI2RZ8S.png https://forum.cogsci.nl/uploads/381/QITYTVTXL9JG.png https://forum.cogsci.nl/uploads/483/1ZHMHFMRU5X3.png https://forum.cogsci.nl/uploads/827/FAR74SD05CEM.png
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you can do it "manually" in the SEM analysis using lavaan syntax
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@TarandeepKang Cool! Great idea, I personally would love to see this arrive in JASP