Thanks for your reply. Here's a watered-down version of the .omv file. Don't mind the model being tested, it is just for testing purposes.

PS: I am getting a "there is no package called rappdirs" error message from my personal computer (that would not go away with installing jvmRedWrite). Hopefully, you get the original error message (long vectors not supported yet).

Regards,

Statistics: Posted by MaximeB — Sun Oct 02, 2022 2:19 pm

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Here I got photo screen for the problem.

Statistics: Posted by Haruka — Sun Oct 02, 2022 11:55 am

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so do results appear straight away (tables, etc.) and it's only plots that take time to load?

with thanks

Statistics: Posted by jonathon — Sun Oct 02, 2022 5:59 am

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cheers

jonathon

Statistics: Posted by jonathon — Sun Oct 02, 2022 5:57 am

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First of all, thank you for making Jamovi freely available. It has been collaborative projects a lot easier than other statistical packages (eg, SPSS).

When doing linear mixed-effect models (LMM), I am used to throwing robust LMM as sensitivity analyses to safeguard myself against potential bias from outlying observations. I normally do this in R with the robustlmm package (function rlmer). However, I wanted to import my script on Jamovi to make it available to my colleagues unfamiliar with R. Running the rlmer function works as intended. However, when I try to compute confidence intervals, I get the following errors:

- Code:
`long vectors not supported yet: array.c:2192`

Given that the code runs correctly on R, I was wondering if the issue came from Jamovi. If this is a known issue, is there a workaround?

I am unable to attach a screenshot to my post, but here's the simple script I have tried to use:

- Code:
`# Make sure Jamovi is using system R (and not Jamovi R) ->`

library(lme4)

library(robustlmm)

# Custom functions ----

# Function given by Ben Bolker on Cross Validated to compute CIs from rlmer

# https://stats.stackexchange.com/questions/233800/how-can-i-get-confidence-intervals-for-fixed-effects-using-the-rlmer-function-r

confint.rlmerMod <- function(object,parm,level=0.95) {

beta <- fixef(object)

if (missing(parm)) parm <- names(beta)

se <- sqrt(diag(vcov(object)))

z <- qnorm((1+level)/2)

ctab <- cbind(beta-z*se,beta+z*se)

colnames(ctab) <- stats:::format.perc(c((1-level)/2,(1+level)/2),

digits=3)

return(ctab[parm,])

}

# Write the formula you want to use in the function below

# Please, make sure the variables are listed above (in the right box)

rlmer <- rlmer(

data = data,

formula = score ~ group * condition + (1|id)

)

summary(rlmer)

confint(rlmer)

Thank you in advance for your help!

Statistics: Posted by MaximeB — Fri Sep 30, 2022 8:09 pm

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Statistics: Posted by RMD — Thu Sep 29, 2022 12:12 am

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RMD wrote:

Does anyone know how I can retain value labels and variable labels and import directly?

Does anyone know how I can retain value labels and variable labels and import directly?

Hey @RMD,

first change the Type of your RespondentID variable from Numeric 8.2 to String 10 and save the .sav file, so jamovi will give you this:

open_sav.png

Cheers,

Maurizio

Statistics: Posted by MAgojam — Wed Sep 28, 2022 7:23 pm

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That is better than 10+ minutes but still not acceptable. I will dig into it a little bit more and I will post my findings here (if any).

Statistics: Posted by Quint — Wed Sep 28, 2022 2:16 pm

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I've managed via conversion through Excel (.sav --> .xlxs --> .omv), but that way I lose the value labels and the variable labels. The error message I'm getting is:

"unable to perform import: Python int too large to convert to C long"

I thought the file could be too long, but it still doesn't work if I shorten it, nor if I shorten and simplify variable names and labels.

Does anyone know how I can retain value labels and variable labels and import directly?

The .sav file is here: https://1drv.ms/u/s!Ak18NDjxZnZr1XMXfy5Vh4i65QRF?e=CMava4

Statistics: Posted by RMD — Wed Sep 28, 2022 5:38 am

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https://www.jamovi.org/cloud.html

jonathon

Statistics: Posted by jonathon — Tue Sep 27, 2022 10:42 pm

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I am going to try and deploy an "out of the box" windows 10 deployment and see what happens.

Statistics: Posted by Quint — Tue Sep 27, 2022 4:40 pm

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but there's not really any other sort of issue that involves a 10 minute delay either! so i'm inclined to think permissions are probably it.

are there any permissions set that might affect named pipe ipc?

jonathon

Statistics: Posted by jonathon — Sun Sep 25, 2022 2:52 am

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Statistics: Posted by Quint — Wed Sep 21, 2022 11:10 am

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this suggests the communications between the main server process, and the background engine processes may be being blocked. this communication relies on named ipc channels.

https://github.com/jamovi/jamovi/blob/current-dev/server/jamovi/server/enginemanager.py#L40-L44

let us know if that looks to be the issue.

cheers

jonathon

Statistics: Posted by jonathon — Tue Sep 20, 2022 11:47 pm

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