Is it possible to detect outliers with missing data?
atanasj opened this issue · comments
I am trying to diagnose some issues with a lavaan
model, however I age getting the error:
Error in forward.search(phd_fin_wide, riclpm_mod) :
All routines require complete datasets (no NA's) so that the search
gives meaningful results.
I can run the model in lavaan
using fiml
… am I doing something wrong?
Could you provide a reproducible example of this issue? It's possible that some methods can work well with missing data, such likelihood-based criteria, but others likely will no work well. In any event, some simple example to reproduce the problem would be appreciated.