Hi, forgive me if you see duplicate messages. I previously posted the question on my last thread. But I think it's more proper to make it as a new topic.
My question is like this:Since I want the missing value of my dataset, whereas FIML doesn't provide that, I chose multiple imputation (MI) to deal with my missing data instead of FIML. The problem is after MI (say, I did 5 imputations), I get 5 imputed datasets. How can I use these datasets to build SEM? Shall I conduct SEM on each imputed dataset separately? If so, how can I combine the model parameters and model fitness indice (e.g. TLI, CFI, RMSEA)?
I find there is one previous thread in this forum talking about the same problem: https://openmx.ssri.psu.edu/thread/118 . It tells that OpenMx cannot deal with the multiple imputed datasets directly, we need to do the combination manually. Can I know the details how to do this manually? Do we conduct SEM separately on each imputed dataset and average all the parameters and weights? Thanks in advance.