Hi Mike,
I am using random-effects MASEM and I would like to include a binary characteristic of the studies in my analysis. Based on your recent paper (Cheung, 2014), I know that mixed-effects model can be used to include study characteristics as the predictors in a MASEM model. However, I was wondering how I can do this using metaSEM codes. I could not find any metaSEM code example in your papers/website that explain how I should code and indicate the study characteristics in tssem1() and tssem2() functions in metaSEM.
Your help would be very much appreciated,
Thank you,
-- Hamed
Cheung, M. W.-L. 2014. "Fixed- and Random-Effects Meta-Analytic Structural Equation Modeling: Examples and Analyses in R," Behavior Research Methods (46:1), pp. 29-40.
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Hi Hamed,
The metaSEM package has not implemented methods to handle continuous moderators in TSSEM yet. It is because I am not sure whether it makes sense to do it. If you really want to do it, you may use the meta() function to conduct a multivariate mixed-effects meta-analysis by scaling the moderators to the appropriate zero value in the first stage of analysis. The intercepts represent the covariate-adjusted correlation matrix. You may extract the intercepts and their asymptotic covariance matrix to fit structural models with the wls() function in the stage 2 analysis. There are issues with this approach. You are on your own risk if you use it.
Since your moderator is binary, a better choice is to conduct two separate random-effects TSSEM.
Hope it helps.
Mike