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!!!!
You have to check this using individual residual plots using the Scatterplot option in the plot menu. Because this works with raw data, you have to do it separately for each imputed data set. For individual residuals, see the paper on our website:
Asparouhov, T. & Muthén, B. (2014). Using Mplus individual residual plots for diagnostic and model evaluation in SEM. Web note 20.