[R-sig-ME] Simulating multilevel dataset

[Stuart Luppescu]

On Fri, 2013-07-05 at 17:25 +0000, Thompson,Paul wrote:
> Well, that's how it would be analyzed. But you have means and
> variability measures to generate the data. Do you have any notion of
> the dependencies/conditionalities inherent in the data? 

The variance-covariances at the individual level are
 3.308523 1.896117
 1.896117 5.694732

at the school level they are

      0.75137       0.59118 
      0.59118       0.93246 

> Are conditionalities additive? Are you considering some variance
> effects?

Not sure what you mean here. I'm not assuming there are any cross-level
interactions, if that's what you're referring to.

> Prior to modeling conditionality, you need parameters to model in the
> direction of.

Again, I apologize for my ignorance, but I don't understand this. The
only parameters in the model are the individual means, variances and
covariances; and the school means, variances and covariances. Do I need
something else?

> -----Original Message-----
> From: Stuart Luppescu [mailto:slu at ccsr.uchicago.edu] 
> Sent: Friday, July 05, 2013 12:19 PM
> To: Thompson,Paul
> Cc: r-sig-mixed-models
> Subject: RE: [R-sig-ME] Simulating multilevel dataset
> 
> On Fri, 2013-07-05 at 16:53 +0000, Thompson,Paul wrote:
> > You indicate that you have teacher level data and the school level
> data. You do not mention data about conditionality. How can you model
> it if you do not have some relationship to model? In addition, you do
> not specify the manner in which error is incorporated into the model.
> 
> The model would look something like this (in lmer notation): meas ~
> var1.indic + var2.indic + (var1.indic|school) + (var2.indic|school)
> Does this address your questions?
> 
> 
-- 
Stuart Luppescu <slu at ccsr.uchicago.edu>
University of Chicago