Grandmean centering in type = twolevel PreviousNext
Mplus Discussion > Multilevel Data/Complex Sample >
 student07 posted on Thursday, August 02, 2007 - 1:23 am
Dear Drs Muthén

I wonder how to use grandmean centering when using (1) type = twolevel and (2)type = twolevel random.

Problem 1: Assume I have a model with both within- and between-level covariates. The model includes random intercepts only and is similar to Ex 9.3. I would like to conduct grandmean centering for the within- and between variables in order to make the intercept more interpretable.

Q#1: Are there any general circumstance where grandmean centering would conflict with the tpye = twolevel approach? I came across this problem because I did not find (perhaps because its so late)any examples in the user guide where grandmean centering is applied for models using random intercepts only.

Problem 2: Assume I have a model with both within- and between-level covariates, and the model includes random intercepts as well as random slopes, similar to Ex 9.1.

I intend to use grandmean centering to mak the slope more interpretable. However it seems that in Ex. 9.1. centering is applied to the WITHIN-(x)variable only, but not for the BETWEEN-(w)variable.

Q#2: Does grandmean centering of within- and between-level variables conflict with the assumptions underlying
"type = twolevel random" ?

P.S.: Is there any literature available which covers the statistical assumptions underlying "type = twolevel random" in the mplus framework?
 student07 posted on Thursday, August 02, 2007 - 2:37 am
May I ask another question: to request
the between- and within covariance matrices
in order to conduct preliminary analyses for a final twolevel factor analysis (step 3 and 4 in Muthén 1994), should one use the MEANSTRUCTURE command such as


and then


SIGB IS Between.dat; !between covariance matrix

SAMPLE IS Within.dat; !pooled within covariance matrix

 Linda K. Muthen posted on Thursday, August 02, 2007 - 8:39 am
Q#1: No.
Q#2: No.
P.S. See the Raudenbush and Bryk book:

Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical linear models: Applications and data analysis methods. Second edition. Newbury Park, CA: Sage Publications.

Yes, but you don't need MEANSTRUCTURE. It is the default with TWOLEVEL.
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