patc3
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That's because JASP has the very, very bad default behavior of including all possible interaction terms as both fixed and random effects. Under Model on the left, remove all terms with a star in it, especially from the random effects box. You might …

Some of your variables in the data view are ordinal instead of scale: https://forum.cogsci.nl/uploads/745/S3C9IQSSVQ2P.png Click on the icon: https://forum.cogsci.nl/uploads/929/H9MQ77XZJC7Y.png Select scale: https://forum.cogsci.nl/uploads/634/UA8E…

Create a new variable that combined both IVs (i.e. a single variable to indicate which cell of the design the person is in)

I don't know your data but the syntax looks fine, what error do you get?

For SEM, assuming you're treating your variables as numeric (scale/continuous), this has to do with fullinformation maximum likelihood (FIML) estimation, which is the default in JASP. If variables are so sparse that it doesn't run, you'll know. Th…

So basically one is standardized and the other isn't?

Can you click Stack trace to show the trace of the error? I just tried process model 4 with my own data, and it worked.

H0 should match the sample mean of the dependent variable, it's simply a regression with only an intercept as predictor. H1 is your model with your selected predictors, in that case the intercept is interpreted as the predicted value on the dependen…

In the analysis panel under model options you should be able to add and remove model terms https://forum.cogsci.nl/uploads/179/5QDBYJH4WK9E.png

Now that you mention it, I'm definitely having the same problem with a big file (a lot of computed vars and a lot of analyses) produced with version 18.0.. just loads indefinitely in 18.2, never opens. Oops :

Are you able to share your original file (which contains your data)? I personally don't know what the problem could be without additional info, I haven't had problems opening 18.1 files in 18.2 (I'm using Windows)

You might find it easier to test this through the ANOVA analysis https://forum.cogsci.nl/uploads/573/L4BTR39BAHVM.png If you want to add numeric predictors as well (which you don't have at the moment), then use ANCOVA instead of ANOVA.

There's no robust vs non robust bootstrap; the choice is between 1) standard SEs, 2) robust SEs, and 3) bootstrap SEs. What bootstrap does is it randomly picks observations from your sample, runs the model, saves the parameter estimates, and repeats…

Yes the difference is how the standard errors are calculated, and no it's not using bootstrap unless you check the box

Pretty sure you can't do RM manova in JASP currently. I'm not on my computer right nowis there a way to specify the error term manually in the MANOVA procedure? Is there a box for random factors? If yes to one of these two questions, you might be …

What you can do is create a new variable that is the combination of several grouping variable, for example using edit data > insert column using R code: paste(gender, agegroup, sep="_") This will create a variable that's the combination…

OK I could reproduce your situation with a dataset that ships with JASP in the data library (14 SEM: Grade point average): https://forum.cogsci.nl/uploads/961/6XL1RZYCHRJ7.png I did a little bit of digging by running the same analysis directly in R…

No it's not because the assumptions are not met. Can you show a screenshot of your analysis and your output?

Actually you're not sending me emails, you're responding on the ticket you made on GitHub 🙂 https://github.com/jaspstats/jaspissues/issues/2476

Unfortunately I don't think there is a way to do this from within JASP currently. In Excel I suspect you could achieve this with the vlookup() function, and in R (if you're familiar with it) you could do it in just a few lines using the full_join() …

Most people treat it as scale.. Actually the opposite (treating a Likert scale as ordered) is quite rare. My guess is they treated it as scale, in most software a Likert scale is treated as scale by default (R, Mplus), but JASP distinguishes betwee…

No it's not possible to use FIML with ordered predictors in JASP (or in the R library lavaan, which JASP uses in the backend). Are you sure the article you're replicating treated them as ordered and not scale? My best guess reading your post is that…

In the "advanced" tab, you can set missing data handling to "listwise". The default (FIML) only works if all your variables are scale. It doesn't work with ULS.

thanks EJ I sent the email

How do we become testers?

wowowow 😍😍😍 I hadn't seen this

JASP is just exceptional... I constantly introduce profs and students to it and usually they stick to it. I too have begun using it alongside R (which used to be my only tool).

perhaps you're looking for "heatmap"

I believe the pvalue will match exactly that of the regression coefficient, as they are "semipartial" effects themselves (i.e. unique variance only)

FYI if I recall correctly linear regression is said to be "robust" to violations of the normality assumption, meaning that even when it is violated the coefficients and their hypothesis tests are OK. (This is unlike the homogeneity of resi…