Hello,
I'm trying to conduct a moderation analysis between a latent variable (job demands) and an observed variable (adaptive coping) moderated by an observed/continued variable (titled mind set) using R package 'lavaan'.
The following part of the code has been implemented and I'm quite sure it's wrong:
##Legend##
jd - job demands (latent variable)
cd - cognitive demands (observed variable)
ed - emotional demands (observed variable)
ac - adaptive coping (observed variable)
mt - mind set (moderator)
##lavaan model##
model.base
I recommend you first create your moderation term outside of your lavaan model using the 'semTools' package command 'orthogonalize'. Using this command you will use centered residuals to create your moderation term as suggested by Todd Little. To make sure you are using his suggested approach make sure you are set matching=false when you use the 'semTools:orthogonalize' command. After you create this term you can use it in your model as a latent factor - it creates indicators for every possible combination between your latent factor indicators and whatever indicators for the other latent factor or observed variable you are creating the term for. make sure you also set covariances between your new moderation latent variable and the variables in the model used to create it to 0 (e.g. interaction_term ~~ 0*jd) . Below is an article that can help.
Little, T. D., Bovaird, J. A., & Widaman, K. F. (2006). On the merits of orthogonalizing powered and product terms: Implications for modeling interactions among latent variables. Structural Equation Modeling, 13(4), 497-519.
I found lav2nlsem function in the nlsem package that allows creating interaction term between latent variables.
https://www.rdocumentation.org/packages/nlsem/versions/0.8/topics/lav2nlsem
But I am still struggling with the coding. If anyone has tried that, could you please let me know if this function allows interaction between a latent and an observed variable? Any provide me a sample code? Many thanks in advance!
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