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 Anne Buu posted on Wednesday, March 26, 2008 - 9:28 am
Q1: Are the factor scores saved by FSCORES calculated by expected a posteriori or maximum a posteriori?
Q2: Are the factor scores calculated by assuming the parameters of fixed effects are known (i.e. filling in the estimates of parameters)?
Q3: Why EFA does not produce factor scores? Is it "technically" not feasible or just "logically" not favored by the Mplus team?
 Linda K. Muthen posted on Wednesday, March 26, 2008 - 11:28 am
1. This varies. For TYPE=GENERAL, categorical dependent variables, and weighted least squares estimation, it is maximum a posteriori. In other cases and for TYPE=GENERAL, categorical outcomes, and maximum likelihood estimation, it is expected a posteriori.
2. Yes.
3. It is basically that if someone asks for factor solutions for one through eight factors, it would end up being a massive file depending on the number of observations. In Version 5.1, there will be a new feature that will allow this in a more limited way.
 Nathan Stein posted on Friday, August 13, 2010 - 12:02 pm
Above, you stated that there will be a new feature in Version 5.1 that will allow factor scores for EFA in a more limited way. Is this true in Version 6? Can we get factor scores from an EFA?
 Linda K. Muthen posted on Friday, August 13, 2010 - 2:17 pm
The ESEM feature which was introduced in Version 5.1 is also in Version 6. See Examples 5.24 through 5.27 and the MODEL command in the user's guide. You can get factor scores with ESEM.
 Johannes Bauer posted on Wednesday, July 03, 2013 - 8:37 am
We estimated factor scores from a cfa model and found that the correlations between the obtained factor scores and the manifest scale means (i.e. average scores over the items belonging to each factor) are close to 0 or even negative. We observed this in two independent data sets and respective cfa models.

Do you have any idea why this is the case?
 Bengt O. Muthen posted on Wednesday, July 03, 2013 - 2:46 pm
That should only happen if the factor determinacy is very low, making the factor scores poor estimates.
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