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 Jean-Simon Leclerc posted on Tuesday, June 20, 2017 - 8:09 pm
Hi, I started reading about missing data handling techniques in Mplus and I'm not sure to what extent are FIML and MI equivalent for my needs.

Here's a little more information on the model. It contains continuous latent variables and has indirect effects and latent interactions. I have two measurement points. My T1 (n=570) data contains missing data for 3 to 10% of observations and my T2 data (n=380), 10 to 30% missing data (many respondents just completed T1).

So here is my question: if I simply used the default FIML for handling missing data, will all the model be fitted for 570 respondents? (as if I had made MI)? And would that be the right technique?
 Bengt O. Muthen posted on Thursday, June 22, 2017 - 1:47 pm
Yes and yes.
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