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Mplus Discussion > Multilevel Data/Complex Sample >
 Michael Bohlig posted on Thursday, May 15, 2014 - 8:26 pm
I have survey data collected at over 350 colleges. My dependent variable is continuous and all independent variables/covariates are binary - group membership indicators. The dependent variable is the mean of several 0-1 variables then standardized to have a mean of 50 and a standard deviation of 25.

All variables in my model are observed and the model is fully saturated.

I have set up a model with the following parameters (skipping Names and usevariables).

cluster is col_id ;
missing are all . ;
within = q16 enrl female dev ;

ANALYSIS: type = twolevel ;

ACC ON q16 fulltime female dev ;

OUTPUT sampstat stdyx ;

The independent variables are all coded as 0/1 where 1 represents the characteristic described by the variable (dev indicates a student is not college-ready - needs developmental courses).

The between level means estimate for ACC is 41.602 with a S.E. of 0.274. The between level variance estimate for ACC is 12.942 with a S.E. of 1.584. The mean estimate for ACC is quite a bit lower than I expected. It has been a long time since I have done this type of analysis so I'm wondering if I have missed something.

I'm planning to expand this model to a intercept and slopes as outcome model, but I want to make sure I understand what I am doing at a less complex level before I move on.
 Linda K. Muthen posted on Friday, May 16, 2014 - 9:57 am
On between ACC is a random intercept. The value 12.942 is the mean of the random intercept. See Example 9.1 in the user's guide.
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