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RE: st: Fw: appling a gamma distribution random effects model. SAS to Stata


From   Nick Cox <n.j.cox@durham.ac.uk>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Fw: appling a gamma distribution random effects model. SAS to Stata
Date   Wed, 7 Dec 2011 11:30:24 +0000

I suspect that Brent would be better off showing the whole of the SAS code so that someone bilingual (emphatically not me) can translate. It has more of a flavour of fitting a model than of generating random deviates to me, but no amount of speculation can replace expertise. 

Nick 
n.j.cox@durham.ac.uk 

Maarten Buis

On Wed, Dec 7, 2011 at 10:31 AM, Brent McSharry wrote:

> I have some SAS code to apply a model to patient data, and I would like to
> apply this to our local data (the model is externally validated to predict
> length of ICU stay in days).
> Unfortunately I have no idea about SAS syntax, and exclusively use stata.
>
> the first part of the SAS code obviously generates a linear coefficient &
> applies an exp link
> ie in Stata:
>
> scalar s2u = 1
> scalar a = 2
> generate linCoef = 0.2 + varA * 0.4 + varB*-0.02 ...
> generate mu= exp(linCoef)
> gen b = mu/a
>
> and then i am affraid I am lost (particularly as the = signs stop and the
> tildas ~ begin)
>
> model los_days ~ gamma(a,b);
> random u ~ normal(0,s2u) subject=varY out=random;
> predict mu out=predout;
> run;

I have no idea about the syntax in Some Alternative Software either,
but the tilde is often used for "distributed as", which makes sense in
your case. I guess you want to create a random variables from that
validated model. Now you need to figure out where exactly the random
term enters the model. I guess it is added to the linear predictor,
but you need to check that in the documentation of that model. You
also need to check the exact parameterization of the gamma
distribution used in that model and possibly translate that to the
parameterization used in -rgamma()-. After that it will be a couple of
-generate- commands calling the -normal()- and -rgamma()- functions,
see -help random_number_functions-.


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