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 Tristan posted on Saturday, March 03, 2012 - 6:13 am
Hi there,

I am new to SEM and MPLUS, and attempting to model a latent factor that influences all indicators in the structural model as per the recommendations of Podsakoff et al (2003). I am getting some weird results when I compare the path coefficients in my structural models (no CMV factor versus CMV factor present). The coefficients (and overall R2 for endogenous variable) differs significantly between CMV and no CMV models, so I want to check if I am modelling CMV correctly. My code is below:

factor definition and path modelling omitted...

CMV by Q9ci_RecWelc-Q29_ServNeeds;

Thanks so much,

 Linda K. Muthen posted on Saturday, March 03, 2012 - 8:44 am
I see nothing wrong in what you present. To answer your question, I need to see the full outputs and your license number at
 Jorge Walter posted on Thursday, July 03, 2014 - 10:39 am
Dear Linda,

I'm working on the same common method test described above. And while my models are working, I was wondering how exactly I could use the output of such a CFA model to partition the variance, i.e., estimate the percentage of variance in responses due to trait, method, and random error components
(Podsakoff et al., 2003; Williams, Cote, & Buckley, 1989)?

Thanks in advance for your help!
 Bengt O. Muthen posted on Thursday, July 03, 2014 - 4:21 pm
You may want to ask this general question on SEMNET. The Mplus Model Constraint command can be used for any such expression.
 Jorge Walter posted on Saturday, July 05, 2014 - 4:21 am
Thanks, Bengt, will do.
 Tunde Ogunfowora posted on Tuesday, February 03, 2015 - 12:31 pm
Hi there,

I am trying to test for common method bias effects in a 6-factor measurement model. Of the six factors, three of them are single indicators (one of which is categorical with two levels).

I have specified the following:


OrgCyn_F by ogcyn1 ogcyn4 Ogcyn2 ogcyn3 ogcyn5;
Ego_Cse_F by Egoist1 Egoist4 Egoist3 Egoist2;
Val_Cse_F by values3 values4 values2 values5;

Ego_Cse_F OrgCyn_F Val_Cse_F voluntr purchse DonatBhv with Ego_Cse_F OrgCyn_F Val_Cse_F voluntr purchse DonatBhv;

CMV_F by voluntr
purchse ogcyn1 ogcyn4 Ogcyn2 ogcyn3 ogcyn5 Egoist1 Egoist4 (a)
Egoist3 Egoist2 values3 values4 values2 values5 DonatBhv (a);

CMV_F@1 ;
CMV_F with OrgCyn_F@0 Val_Cse_F@0 Ego_Cse_F@0 ;

My understanding is that constraining all variables to load equally on the CMV factor allows one to compute the proportion of variance explained by the CMV factor. This is why I have constrained using (a).

However, I am also interested in testing changes in model fit between the 6-factor model and the 7 factor model. Constraining the factor loadings (a) gives a different chi-squared estimate compared to the unconstrained model. Can you please educate me on which of these is appropriate?
 Tunde Ogunfowora posted on Tuesday, February 03, 2015 - 12:32 pm
Also, do I have to specify anything for the single item variables? For instance, do I have to specify the following separately?:


Lastly, do I have to specify correlations (equal to zero) between the CMV factor and the single item variables like i did for the latent variables? Specifically:

CMV_F with DonatBhv@0 purchse@0 voluntr@0;

Thank you for your help!

 Bengt O. Muthen posted on Tuesday, February 03, 2015 - 4:44 pm
You want to ask these general modeling questions on SEMNET which is a more general discussion forum.

Also, we ask the no more than one window is used for Mplus Discussion.
 Tunde Ogunfowora posted on Wednesday, February 04, 2015 - 9:05 am
Hi Bengt,

I will look into SEMNET for my general SEM questions. However, can you please let me know if my MPLUS syntax is appropriate for what i am trying to achieve:

Specifically, do I have to specify the following lines for my single item factors? This is a Mplus specific coding question.



 Bengt O. Muthen posted on Wednesday, February 04, 2015 - 3:21 pm
No, you just use the variables in the ON or WITH statements you have in mind.
 Tunde Ogunfowora posted on Wednesday, February 04, 2015 - 3:35 pm
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