FIML (full information maximum likelihood) in R for Missing Data in Multilevel Model Has anyone been able to find any package/function to run FIML in R for multilevel models? I know the lavaan package has a function for it, but it doesn't support mlm. I've only been able to find it in MPlus, but I do not know how to work the program (so I am trying to find a way to avoid going in MPlus to do this). Initially, the lmer function simply applied listwise deletion to my data, but I ended up with lots of missing data (my study was a daily diary study with two respondents), so reviewers have asked me to do FIML instead.
I used the md.pattern function of the mice package to look at my missing data and right now it looks like I have 11 variables with missing data (with a total of 427 missing cases, 1328 missing cases).
If not, is there another free-to-use program (that is beginner friendly) that allows me to run my multilevel models with FIML?
Please know that I am a beginner in R (and any analysis program to be frank). Thank you!

This post shows how to use FIML with multilevel data using lavaan.
https://francish.net/post/accounting-for-missing-data-mlm/
