

Multilevel random effects metaanalysis 

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Hello, I am working on a multilevel 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 


You cannot use a level 2 predictor on level 1. You may be wanting a crosslevel interaction. See Example 9.2 in the user's guide. 


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: %WITHIN% s  x on y; %BETWEEN% s; [sw]; [x@0.0]; x@1.0; x on z; Thank you! 


I apologize for the error above  I meant [s]; not [sw]; 


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. 


Hello I am working on a 3 level metaanalysis. 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 twolevel metaanalysis (on slide 157): https://www.statmodel.com/download/Topic9v52%20%5BCompatibility%20Mode%5D.pdf 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; USEVARIABLE = y A_SB x; CLUSTER = Cluster Id; WITHIN = y x; BETWEEN = (Cluster) A_SB; DEFINE: y = y/sd; x = 1/sd; ANALYSIS: TYPE = THREELEVEL RANDOM; ESTIMATOR = ML; MODEL: %WITHIN% [y@0.0]; y@1.0; theta  y ON x; %BETWEEN Id% theta; %BETWEEN Cluster; theta ON A_SB; Is this correct? Thank you! 


Looks like it is on the right track. 

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