Rj editor: long vectors not supported yet
Posted: Fri Sep 30, 2022 8:09 pm
Hello Jamovi Team,
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:
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:
Thank you in advance for your help!
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: Select all
long vectors not supported yet: array.c:2192I am unable to attach a screenshot to my post, but here's the simple script I have tried to use:
Code: Select all
# 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)