Assumptions such as linearity of rela... PreviousNext
Mplus Discussion > Structural Equation Modeling >
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 Elina Dale posted on Saturday, October 19, 2013 - 9:16 am
Dear Dr. Muthen,

I've just realized that unlike with regression models where we have observed predictors and outcomes, in SEM I do not know exactly how to check the assumptions such as linearity of relationship between factors (predictors in this case) and an observed outcome.

I am modeling motivation factors as predictors of intention to stay (measured as observed continuous variable). I am not sure how to check in MPlus after I run my model whether assumptions of the model hold. I can see global fit indices but they don't show how well our assumptions (including linearity) hold, do they?

Thank you very much for your guidance and help!!!!
 Bengt O. Muthen posted on Saturday, October 19, 2013 - 3:35 pm
That's right, global fit indices don't tell you if structural relations are linear or not.

You can estimate factor scores and see if the relationships look linear.
 Elina Dale posted on Saturday, October 19, 2013 - 4:38 pm
Thank you, Dr. Muthen! Do you mean that I'd use those factor scores as observed variables in my regression models and do the usual diagnostics (like looking at residuals)?

So, instead of treating motivation factors as latent variables, I'd treat them as if they were observed.
 Bengt O. Muthen posted on Saturday, October 19, 2013 - 5:00 pm
I would simply plot the factor scores against each other.
 Linda K. Muthen posted on Saturday, October 19, 2013 - 5:26 pm
No. You would use the factors scores as proxies for the factors to check the linear relationships. You would treat the motivation factors as latent variables in your model.
 Elina Dale posted on Saturday, October 19, 2013 - 7:05 pm
Thank you so much, Dr. Bengt Muthen and Dr. Linda Muthen! This is very helpful!
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