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 Sara Douglass posted on Wednesday, May 23, 2012 - 10:24 am

I am working on a multi-level meta analysis. The model we have has a continuous Level 1 outcome, a continuous Level 1 predictor, and a continuous Level 2 predictor. I have been able to easily fit a fixed effects model to the data in MPlus, and would like to now fit a random effects model. However, I am running into serious issues with this model, and in looking more closely at the available examples for such analyses I have noticed that they all only use Level 1 predictors. Indeed, when the Level 2 predictor is excluded, the random effects model runs just fine. I am wondering if it is possible to estimate such a model including a Level 2 predictor, and if you might be able to point me to any references regarding this type of analysis?

Thank you,
Sara Douglass
 Linda K. Muthen posted on Wednesday, May 23, 2012 - 12:19 pm
You cannot use a level 2 predictor on level 1. You may be wanting a cross-level interaction. See Example 9.2 in the user's guide.
 Sara Douglass posted on Wednesday, May 23, 2012 - 12:29 pm
Sorry, let me clarify:

Is it possible to just include a Level 2 predictor, at Level 2, while modeling a random slope at Level 1. For instance:

s | x on y;
x on z;

Thank you!
 Sara Douglass posted on Wednesday, May 23, 2012 - 12:29 pm
I apologize for the error above - I meant [s]; not [sw];
 Linda K. Muthen posted on Wednesday, May 23, 2012 - 3:56 pm
The variable x must be on the WITHIN list when it is used as part of a random slope. So x cannot appear on between. See Example 9.2.
 Christoph Nohe posted on Tuesday, June 30, 2015 - 12:27 am
I am working on a 3 level meta-analysis. In my data, the effect sizes (= level 1) are nested under samples (= level 2) which are nested under countries (= level 3). In your handout, I found code for a two-level meta-analysis (on slide 157):

My understanding is that in your code ID is the unique identifier for each level 2 cluster (samples in my case). I would like to apply your approach to 3 level data. In addition, I would like to test a level 3 moderator. As in your code, ID is the unique identifier for each level 2 cluster (= samples). CLUSTER is the unique identifier for each level 3 cluster (= countries):

VARIABLE: Names = Cluster Id y sd A_SB;

CLUSTER = Cluster Id;
WITHIN = y x;
BETWEEN = (Cluster) A_SB;
DEFINE: y = y/sd;
x = 1/sd;


theta | y ON x;


%BETWEEN Cluster;
theta ON A_SB;

Is this correct? Thank you!
 Bengt O. Muthen posted on Wednesday, July 01, 2015 - 5:17 pm
Looks like it is on the right track.
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