Missing values level 2 covariate PreviousNext
Mplus Discussion > Multilevel Data/Complex Sample >
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 tino posted on Monday, June 04, 2012 - 4:07 am
Hi

in a twolevel regression model, how can I compensate for missing values in a level-2 covariate which is only measured at level-2 (varies only between-groups)? FIML only works for dependent variables, correct?

thank you for your answer
 Linda K. Muthen posted on Monday, June 04, 2012 - 10:21 am
You can mention the variances of the covariates on between. Then they will be treated as dependent variables and distributional assumptions will be made about them but observations with missing on them won't be deleted. You must include all covariates.
 tino posted on Monday, June 04, 2012 - 1:47 pm
ok, this sounds like an interesting approach - but is there a reference for this approach, is this fiml or just similar to fiml?
 Bengt O. Muthen posted on Monday, June 04, 2012 - 5:43 pm
It is full-information maximum likelihood - you are just moving the approach up a level, but it's perfectly analogous. I am not aware of papers on it. If you do multiple imputations you would get similar results.
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