patc3
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You can perform rotation using the UI directly in JASP (e.g. in the principal components analysis or the exploratory factor analysis). There's dropdown menus there to select which kind of rotation. edit: sorry I just saw you're trying to get $rms fr…
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Seeing as you're using Gaussian with identity link, have you tried using lineard mixed instead of generalized linear mixed? (Linear mixed is Gaussian with identity link)
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What I meant was I'm pretty sure it actually is equivalent to an ANOVA, not just "like" an ANOVA. That's how an ANOVA is done in the Bayesian framework. If you compare results, pretty sure they'll be basically identical (within Monte Carlo…
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Hmm, I don't know any other way than through a hierarchical model to estimate a RM-ANOVA in the Bayesian framework (that's how I learned it anyhow, through the Kruschke book). Hierarchical models are much more natural (and prevalent) in the Bayesian…
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There is a bona fide RM-ANOVA under the ANOVA menu, select repeated-measures ANOVA (with post-hoc comparisons and effect sizes and the whole shebang): https://i.imgur.com/TugifUG.gif https://i.imgur.com/TugifUG.gif
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Sorry not off the top of my head... you can go on Google Scholar and search for "multilevel logistic regression" or something like that, for example: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5935148/
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Yes, in mixed models > generalized, with binomial family and logit link function
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No need for model <- "...", only the model in the dialog box. No quotation mark, no assignment to a variable called model. Only the model syntax
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Pretty much the same syntax, except that formative constructs (i.e. composite variables) are specified using the <~ operator (e.g. "f1 <~ item1+item2+item3+item4) You can probably get more info by clicking on the "i" information…
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The simplest in your case is to download a previous version of JASP: https://jasp-stats.org/previous-versions/ Note that it's very hard to get an idea what the problem is if you don't give any information about the problem/error received/screenshot/…
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You might have one row (or several) that have something other than a number? or if some of them are blank, maybe it's a space?
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See my comment on another thread here: https://forum.cogsci.nl/discussion/comment/27658#Comment_27658 The answer to your question is probably no, it's difficult to compare continuous and categorical predictors together
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I don't think it'll matter in that case. Not sure it would ever matter in JASP (I don't know), but for correlation and regression the variables shouldn't be treated differently whether they are scale or ordinal.
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What analyses do you want to do with these variables? Also, how many distinct values do they have?
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Again, this could still be due to the interaction terms. Have you tried including age without interaction terms? My guess is still that the problem is due to interaction terms with latent variables. I have personally never dealt with this problem, b…
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I don't know for sure what the source of your problem is, but just bouncing ideas here: I don't think interaction terms with latent variables are implemented in lavaan (the SEM library JASP uses) yet
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I've now discovered that the default model in the mixed-models module is way too complex: by default, all possible interaction terms are included as fixed effects (under the Model section in the analysis), and all possible random slopes (including i…
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the reason is they're not really meaningful with categorical predictors. A standardized coefficient is the effect of x on y when both x and y have been standardized, which means they each have had the mean subtracted from their values, and divided b…
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Hi Mikel, it's really tough to see where the problem is without seeing what the data look like... What about Congruency, are you sure it's only got 2 different values? I'm bothered by the fact that it's a text variable Some descriptive statistics mi…
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I think it's because those are so-called adjusted means, i.e. means adjusted for the effects of the other factors included in your ANOVA. What happens if you test with a simple one-way ANOVA (only your factor)? In that case the means probably match …
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With repeated measures ANOVA you get listwise deletion, i.e. any observation with a missing data anywhere on your 3 assessments will be removed from the analysis. This is not specific to JASP. You should look into mixed effects models instead. Take …
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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…