Tristan posted on Saturday, March 03, 2012 - 6:13 am
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:
MODEL: factor definition and path modelling omitted...
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)?
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?
baozhenzhou posted on Saturday, April 25, 2015 - 12:39 am
Hi there, I'm working on the same common method test described above. However, when i put the latent cmv factor into the CFA model, the model became no convergence,and the number of interactions is exceeded.Could you tell me how can i solve this problem? Thanks very much!
baozhenzhou posted on Saturday, April 25, 2015 - 2:04 am
Hi there, I'm working on the same common method test described above. However, when i put the latent cmv factor into the cfa model, the model became no convergence and the number of iterations is exceeded. Could you tell me how can i solve this problem? Thanks very much!
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Jeff Shao posted on Wednesday, October 05, 2016 - 2:30 pm
I want to ask a question with regard to the Tristan's (the first person in this discussion chain) and Tunde's (the sixth person in this discussion chain) codes. why restricting the variance of the method factor to 1? for example: CMV@1 and CMV_F@1?
Jeff Shao posted on Wednesday, October 05, 2016 - 2:40 pm
In Williams, Cote, and Buckley (1989), the authors calculated the variance partitioning for traits, methods and errors. Can anyone tell me how they made the calculation, please?
In the paper, it says "for each measure, the square of the trait factor loading indicates the percentage of variance due to the trait factors, and the square of the method factor loading indicates the amount of variance due to the method factor". However, there are several factor loadings for each latent variable. How to calculate a single variance score as the authors did in the paper to indicate how much the method factor explains the variance?