jamovi

https://dspace.mit.edu/handle/1721.1/128459

I think violin or boxplots would be more appropriate in your case

This may help
https://www2.karlin.mff.cuni.cz/~pesta/NMFM404/glmm.html#Interpretation

It seams to be not available currently in Jamovi.
You can try doing it using R-based StatsNotebook or simply using R directly..
https://statsnotebook.io/blog/analysis/matching/

This was produced by Flexplot module in jamovi. You may contact developpers for equation or you can add it as text..

Does this help?
https://bookdown.org/pkaldunn/SRM-softw ... ySide.html

from https://data.library.virginia.edu/interpreting-log-transformations-in-a-linear-model/ Only the dependent/response variable is log-transformed. Exponentiate the coefficient, subtract one from this number, and multiply by 100. This gives the percent increase (or decrease) in the response for ever...

Hello everyone
My question : Is the example here
https://gamlj.github.io/mixed_example2.html
the same as "generalized linear mixed models" ?

If not, how to run GLMM using gamlj?
Thanks again for your time

Thank you

I tried it and here is the output:

Output:

Based on this page, https://search.r-project.org/CRAN/refmans/jmv/html/logRegBin.html I think it may be something like this code: data('birthwt', package='MASS') dat <- data.frame( low = factor(birthwt$low), age = birthwt$age, bwt = birthwt$bwt) jmv::logRegBin (data = dat, dep = low, covs = vars(age...