

Control variables in mediation model 

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I am evaluating a mediation model with an independent variable, two mediating latent variables, and a dependent variable. I have three control variables (age, SES, and ethnicity)for which I want to account in the model based on significant bivariate correlations with indicator variables. Where is it best to include them of the following options? 1. Regress the indicator variables with which these are correlated directly on the control variables? 2. Regress the latent variable with which at least one indicator variable is correlated with a control variable on that control variable? 3. Some other method? Is it correct to have these control variables in multiple places in the model (i.e., regressed on both latent variables if appropriate)? Thank you! 


You should use the approach in number 2. 


Dear Professor(s) Muthen, I would like to follow up on this thread. I would be interested in the answer to the second question: Is it correct to have control variables in multiple places in the model (i.e., regressed on both latent variables if appropriate)? My example is the following: What is the difference between the following two syntaxes: PRmeri BY eqOPP rewEFF IQ; PRmeri on male edu age age2 empl; rJP on PRmeri male edu age age2 empl; VS. PRmeri BY eqOPP rewEFF IQ; PRmeri on male edu age age2 empl; rJP on PRmeri; Are the controls for my second equation needed? Or had Mplus already "done the job"? Does Mplus work with already the partial correlations? Thank you in advance for your help, Zsofia Ignacz 


In you second option, you leave out male edu age age2 empl. Mplus will not control for these variables if they are left out. I suggest using option 1. 


Dear Professor Muthen! Thank you very much for your quick answer! Kind regards to you, Zsofia Ignacz 

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