In time series analyses, I have used multi-level or random/mixed effects to deal with auto-correlation issues (i.e., observations are clustered within individuals over time) and added controls are added for some specification of time and for shocks of interest. ARMA/ARIMA seem designed to address similar issues.
The resources I've found online discuss either ARMA/ARIMA or mixed effect models but I don't understand the relationship between the two. Might one want to use ARMA/ARIMA from within a multilevel model? Is there a sense in which the two are equivalent or redundant?
Answers or pointers to resources that discuss this would be great.