RE: st: multilevel logistic model on aggregated data

[Maria Paola Caria <Maria.Paola.Caria@ki.se>]

Thanks Joerg.
I did not explain well. 
the original outcome is individual binary (say, current smoking  yes or not).
but I do not have original data, only aggregated data. so the outcome is now the proportion of smoking students in the class. I think I should model this proportion with a logistic model (since the underlying distribution is binomial) using weights for the numerosity of the class. but then  I want to add the random intercept.




Maria Paola Caria
PhD student
Dept. of Public Health Sciences
Division of Public Health Epidemiology
Karolinska Institutet
SE-11891 Stockholm, Sweden
E-mail: Maria.Paola.Caria@ki.se
________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Joerg Luedicke [joerg.luedicke@gmail.com]
Sent: 22 November 2011 14:58
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: multilevel logistic model on aggregated data

I am not sure if I understand the problem correctly and maybe I am
missing something, but if you do not have any individual level data
you can only look at the variability of schools across countries as,
for example, in:

xtmelogit binaryoutcome x1  x2  || country:, or


Joerg


On Tue, Nov 22, 2011 at 4:58 AM, Maria Paola Caria
<Maria.Paola.Caria@ki.se> wrote:
> I need to fit logistic models on data aggregated at the school level.
> Since there is a hierarchy in the data with schools clustered in regions,
>  I need to add a random intercept  at the region level.
> To clarify, If I had data at the individual level my model would be:
>
> xtmelogit binaryoutcome x1  x2  || country: || school: , or
>
> gllamm binaryoutcome x1 x2, i(school country) eform  family(binomial) link(logit)
>
> but data are aggregated at the school level.
> Is there a command to fit multilevel logistic model on aggregated data in StataSE 12 ?
> Any help is appreciated.
> Thanks.
> Maria Paola
>
>
>
>
>
>
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> Maria Paola Caria
>
> PhD student
>
> Dept. of Public Health Sciences
>
> Division of Public Health Epidemiology
>
> Karolinska Institutet
>
> SE-11891 Stockholm, Sweden
>
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