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I attended a presentation where the Auxiliary feature in Mplus was discussed. A main part of the presentation was that auxiliary variables (Z) can contribute information to the relationship estimation between the dependent (Y) and independent (X) variables  even in the presence of missingness of Y or X. It was stated though, that  if an observation is missing Y *and* X, but contains Z  this observation is not removed and still contributes to the model estimates. Could you please provide an answer or reference about how this is done? I am new to Mplus. Thanks much. 


It does contribute to the model estimates – here is a simple example – suppose that Z is a perfect indicator for Y (i.e. when Y and Z are both observed Y=Z) – then adding the auxiliary Z will make Y always observed (essentially) and thus the mean of Y will depend on Z and those observations where Z is the only observed value. For further information see, http://statmodel.com/download/AuxM2.pdf 

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