Sven Lohrey posted on Saturday, February 21, 2015 - 8:26 am
This question is not only addressed at the Mplus support team, but all of you: I want to test a relationship between two group-level variables (leadership and group climate), while controlling for a number of individual-level variables (gender, age, personality). Optimally, I want the individual-level controls to be group-mean centered, while the group-level predictor should be grand-mean centered. I came up with three different options to do this and would value your input.
1) I could run this as a single-level model, in which I include the aggregated versions of my individual-level controls. I could then group-mean center the aggregated versions of the controls, and grand-mean center leadership.
2) I could run a multilevel model in which I regress the individual-level controls on the individual-level version (i.e. the unaggregated version) of group climate, and then regress leadership on the between-part of the same unaggregated version of group climate. The problem I see with this model is that I cannot grand-mean center group climate on the between level.
3) I could run a multilevel model where I use the unaggregated and group-mean centered version of group climate on the within-level, and the aggregated and grand-mean centered version of group climate on the between level, and specify them beforehand as within/between variables, respectively.
What do you think is the best option?
Sven Lohrey posted on Saturday, February 21, 2015 - 10:57 am
Self-correction: Of course I cannot group-mean center aggregated variables in option 1) and the outcome will remain uncentered in option 2)... also, 2) would give me a cross-level effect, ruling out this option. Maybe I should not work on Saturdays...
I like option 3). If small group sizes I would consider replacing the between-level group climate with its latent counterpart, doing the Mplus decomposition discussed in the Ludtke et al article on our website.
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Sven Lohrey posted on Monday, February 23, 2015 - 2:45 am