patc3
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Wow, thanks for the tip, you're right it's well hidden--I told a student recently that JASP didn't seem to do multinomial logistic regression just yet!
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1) changing the reference category: In the data view, click on the variable name, the reference category will be the first value at the top. To change the order of the values, you can select a row and use the up and down arrow. So you can put the ca…
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Under "Options", test method (on the left) is set to Satterthwaite by default, you can change it to Likelihood ratio tests, like so: https://forum.cogsci.nl/uploads/747/23YCGD1MPDFP.png The output now shows ML estimation: https://forum.cog…
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Yesterday I discovered that the current version has a new bug with the correlation analysis where you can't check/uncheck correlation types or else you get a table full of NaNs... The warning (which says it'll be fixed in 0.17.2) says to refresh the…
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The JASP manual has decision trees at the end to help you choose which test to use: https://jasp-stats.org/wp-content/uploads/2022/04/Statistical-Analysis-in-JASP-A-Students-Guide-v16.pdf More generally you should take a look at the JASP website, th…
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one of your factors has fewer than 2 observations in one of its levels
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In the meantime it might be possible for you to manually create time variables (e.g. time1 = 0 1 2 2 2 and time2 = 0 0 0 1 2 3 has two splines/one turning point) There's a section on piecewise models in Coulombe & Selig (2015), as well as in the…
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this is just to choose the number of components/factors, not how the actual analysis is conducted. So while I'm not an expert in this I suppose if you're doing PCA it makes more sense to choose the number of components with the parallel analysis bas…
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The test is descriptives is univariate (i.e., does each variable follow a normal distribution indiviodually?), while the test in the correlation analysis is either bivariate (do both of my variables taken together follow a bivariate normal distribut…
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Thanks EJ, #1 and #3 are great news
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using R code you can do: rowMeans(cbind(var1, var2, var3), na.rm=TRUE)
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Factor A: F= -1.02e-12 (on R) vs. F=2.878 x 10^-5 (JASP) Hmm negative F-test isn't even possible...
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Hi JP21, I suppose you've done this already but while waiting for the user guide, you can take a look at the documentation for the linear mixed models analysis in JASP by click the "i" button in the analysis
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Can you show an example of SPSS syntax of the analysis you want to replicate? (if you're going through the dialog boxes in SPSS, click "Paste")
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to specify which paths are equal across groups, you need to set the labels to be the same across groups. For example, if you have two groups and want to fix the factor loading of cm1 to be equal across groups, your last line would be: "cm =~ c(…
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It looks like JASP v0.17 uses FIML by default for both CFA and SEM, and you can change this option. If you prefer to use the SEM analysis in JASP instead of the CFA analysis you can specify the syntax for the measurement model manually (e.g. f1 =~ i…
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This might not be ideal but as a temporary fix in the machine learning module you can uncheck "Scale variables" under "Training Parameters" (both for decision tree and SVM) For the regression module you get the coefficient of det…
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Btw I tried some stuff but couldn't figure it out either... am curious to see as well
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Seems to say you have fewer than 2 people in some group(s) in "prlang"
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Edit: Sorry I spoke too fast, I tried with a factor predictor with more than 2 levels and I'm no longer reproducing the fixed effects, seeing as I would need to change the coding as you mention How did you get the chi-square in R? when I do the foll…
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Hello, I'm also curious about this (seeing as the results are *very* different). Could I also check out the data or jasp file? My email is patrick.coulombe@d22consulting.com By the way R-hat of 1.145 seems to indicate the chains have not converged (…
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(Adding info here for readers) The source of the discrepancy has been found and fixed: the number of principal components rather than the number of factors was being retrieved by JASP from the parallel analysis. See the corresponding pull request on…
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@jpe @EJ I'm a little late to the show but the source of the discrepancy has been found and fixed: the number of principal components rather than the number of factors was being retrieved by JASP from the parallel analysis. See the corresponding pul…