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RAM as input to ACE (modelling items as factors, then conducting biometric analysis of these factors)

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tbates's picture
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Joined: 07/31/2009 - 14:25
RAM as input to ACE (modelling items as factors, then conducting biometric analysis of these factors)

We wish to test a bivariate Cholesky model, but using a CFA of raw items as input (rather than scale scores).

What springs to mind is to build a raw-data RAM-based CFA, and then use the individual-level cells representing latent variable scores as input to matrix-style models in a twin analysis.

The RAM models optimise against the raw data, and the Matrix models would take no data, and optimise against the RAM latent factors.

Does that make sense? Any examples floating around? Or alternative approaches (hierarchical factor model and Cholesky all in one, I guess?

neale's picture
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Joined: 07/31/2009 - 15:14
Common Pathway?

If the number of items is not large (

You could, as you suggest, use factor scores as input for a second step in the analysis. This does carry the disadvantage that except under rather unusual Rasch model conditions, not all factor scores are created equal. That is, they differ in their error of measurement. Of course, this is frequently an issue with sum scores or scale scores generally, the analyses of which the literature is replete. Only the odd purist amongst us seems to mind :).

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