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Mplus Discussion > Multilevel Data/Complex Sample >
 Lucy Barnard posted on Sunday, October 07, 2007 - 6:28 am
In doing some multilevel modeling, my ICC appears to be quite low (barely .01). My thought is that it would be foolish to run a multilevel model with such a low ICC. To still acccount for this very slight effect of clusters, I was thinking I should run the analysis in TYPE=Complex as conceptually and by design there are in fact clusters. Please tell me if that's logical enough. :-)
 Linda K. Muthen posted on Sunday, October 07, 2007 - 8:45 am
It is not the size of the intraclass correlation alone that determines whether non-indpendence of observations needs to be accounted for. It is the design effect which is a function of the size of the intraclass correlation and average cluster size. TYPE=TWOLEVEL and TYPE=COMPLEX are two different ways to take non-independence of observations into account. With TWOLEVEL, non-independence of observations is modeled. With COMPLEX, it is taken into account. The choice depends on whether you want to know something about the cluster-level parameters or just control for non-independence of observations.
 Lucy Barnard posted on Sunday, October 07, 2007 - 4:03 pm
Thanks Linda!
 Matthew Cole posted on Monday, October 08, 2007 - 7:10 am
Hi Lucy,

I would also calculate the Design Effect which is based on the ICC and the average cluster size, where DEFF = 1 + (Average cluster size - 1)*ICC. If you find that DEFF >= 2, then you should address the clustering.
 Linda K. Muthen posted on Monday, October 08, 2007 - 6:00 pm
Note that this formula holds for means with equal cluster sizes. It is probably a decent approximation in other cases though.
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