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 ljc posted on Friday, February 07, 2014 - 7:45 pm
I am trying to use esem multiple group analysis like one-way anova to do bivariate analyses with my factors. I have about 20 categorical variables that I want to do bivariate analyses on. Later I would like to do multivariable analyses with the factors and the classification variables.
The problem is that each grouping variable gives me a different version of the factors. I have to make different modifications to achieve partial invariance with each grouping variable. With some grouping variables I canít achieve partial invariance at all and with other grouping variables the interpretation of the factors is different than the interpretation in the total sample.
Am I using the technique appropriately? Any suggestions on a better way to approach this? Or should I just conclude that my factors are too unstable to work with?
 Linda K. Muthen posted on Sunday, February 09, 2014 - 9:17 am
It seems your factors may be too unstable.
 ljc posted on Monday, February 10, 2014 - 7:22 am
One of the criticisms of EFA is that you get a different answer with every sample.

Do you know of any papers or unpublished studies in which an EFA survived more than a few multiple group analyses without falling apart. Thank you.
 Bengt O. Muthen posted on Monday, February 10, 2014 - 11:22 am
I don't think such a critique of EFA is valid. It may instead be that EFA is often applied to measurements that have not been well designed and piloted to measure a certain set of hypothesized constructs.

I am sure the literature contains many studies where the measurement structure holds up. Perhaps you find some in the work by Marsh et al at

You can also try out the Holzinger-Swineford data on our web site and study school, gender and age differences - you will find that the EFA structure holds up well.
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