Dear Linda and/or Bengt, I have a data set with 1042 subjects that I am using for a CFA of a measure with 23 categorical items. We also have 4 grouping variables in the data for doing invariance analyses. When I run any model other than a unifactorial model with imputation of missing data, Mplus tells us there are 1042 observations as it should and without missing data it tells us there are 1012 observations (the number of cases with complete data). However, when we try to run a unifactorial model, with imputation of missing data, Mplus tells us there are only 521 observations, and without missing data imputation it tell us there are 503 observations.
Also, when we ask for a difference test between the unifactorial model and a 3-factor oblique model or (equivalently) a higher-order model with one second-order factor and 3 first-order factors, Mplus will not give us a difference test if we impute missing data (telling us the models aren't nested) but it will do so if we don't impute missing data (though it tells us that the number of observations is 503).
Even stranger (to me at least), in our multiple group CFAs (testing invariance) the unifactorial model runs just fine including the difference tests and with the correct number of observations.
Any help you can give us will be much appreciated as we are trying to get the revision of ms ready to resubmit. best, Rick Zinbarg
I am not sure what you mean by running "a unifactorial model with imputation of missing data". Mplus does not do imputation of missing data - perhaps you mean running with Type=Missing? Analyzing the same set of observed variables using Type = Missing should give the same sample size irrespective of the model. It sounds like it is best if you send this to support.
Just for the record, in case anyone is following this particualr discussion thread other than me, this was not a problem with Mplus but rather the result of a stupid syntax error on my part. Rick Zinbarg