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Re: st: How do I interpret random coefficient parameters (SD) using xtmixed


From   "Miller, Daniel P" <dpmiller@bu.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: How do I interpret random coefficient parameters (SD) using xtmixed
Date   Sun, 17 Jul 2011 18:27:27 -0400

The other thing to look at is whether the random effects terms are significant or not. Significantly different from zero indicates unexplained variation in your dependent variable at whatever level you are examining.

If you are referring to any standard MLM text you might also check to see if the ucla stat website has a chapter by chapter walkthrough as this can be helpful in seeing how book examples are run and interpreted.

www.ats.ucla.edu/stat/examples

Dan

Sent from my iPhone

On Jul 17, 2011, at 5:47 PM, "Owen Gallupe" <ogallupe@gmail.com> wrote:

> Hi,
> 
> I'm no expert on the subject, but this is my understanding. Unless I'm
> mistaken, those are standard deviations across the different countries
> in your analysis. This tells you whether or not there is much
> difference in your variables across countries. So, sd(livsit1) = 3.346
> tells you that the standard deviation across countries is 3.346 on
> livsit1...it's up to you to interpret whether or not this is large.
> 
> sd(_cons) is the standard deviation of the intercept across countries.
> If this is substantially large, it justifies running a random effects
> model.
> 
> By using an unstructured covariance matrix [if appropriate - xtmixed
> w_dur livsit1 || country: livsit1, mle cov(un)], you would also get
> the correlation between the random intercepts and random slopes (in
> your case, between sd(livsit1) and sd(_cons)) which can be
> informative. For example, if corr(livsit1, _cons) is positive, that
> would mean that countries with a higher intercept (higher mean scores
> on the dependent variable) also tend to have a steeper slope on
> livsit1. That is, the effect of livsit1 on w_dur tends to be higher
> when the country has a higher level of livsit1.
> 
> A quick search turned up this page which might be useful:
> http://dss.princeton.edu/training/Multilevel101.pdf
> 
> Hope this helps.
> 
> Owen
> 
> 
> 
> On Sat, Jul 16, 2011 at 1:06 PM, Zachary Zimmer
> <zachary.zimmer@ipia.utah.edu> wrote:
>> I am running random coefficient models using xtmixed assuming there are different intercepts and slopes for variables across different countries.
>> 
>> For instance, using the STATA command:
>> . xtmixed w_dur livsit1 || country: livsit1, mle
>> the intercept and slope of livsit1 when estimating the dependent variable w_dur for is allowed to vary across county.
>> 
>> The Random-effects Parameters are:
>> 
>> sd(livsit1) = 3.346
>> sd(_cons) = 1.889
>> sd(Residual) = 28.601
>> 
>> Can someone tell me how specifically to interpret these parameters?  What does the 3.346 mean?  Etc.
>> 
>> Thanks for any help.
>> 
>> 
>> Zachary Zimmer
>> Professor, Department of Sociology
>> Senior Scholar, Institute of Public and International Affairs
>> University of Utah
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