Re: st: logistic regression complex samples

[Stas Kolenikov <skolenik@gmail.com>]

Antonio,

it would help if you mentioned the version of Stata that you are
using. By default, Stata would use observations as PSUs (and the
output of -svyset- would state that -- again, it would help if you
included the output of both commands). You can also achieve the effect
of specifying observations as PSUs via -svyset _n ...-.

On Wed, Dec 7, 2011 at 10:05 AM, Antonio silva <asilva@inbox.com> wrote:
> Hello,
> I would like to perform binary logistic regression in stratified sampling incorporating 2 variables that represents that design var_weight and var_strata.
> Considering a model with 2 covariates , in SAS I would consider a code like this that works perfectly:
>
> PROC SURVEYLOGISTIC DATA =  dataset
> STRATA var_strata;
>
> WEIGHT var_weight;
>
>
> CLASS covariate1
>      Covariate2  ;
>
> MODEL outcome(event='1')= covariate1 covariate2 /clparm vadjust=none ;
>  Run;
>
>
> I tried an equivalent Stata code but does not work. It seems that in Stata its is always necessary have the cluster variable. But in my design I do not have cluster variable,only weight and strata.
>
> svyset [pweight= var_weight], strata(var_strata)
>
>  svy: logistic outcome i.covariate1 i.covariate2
>
> After run , in the output appears only the OR calculated and a note:
> Note: missing standard errors because of stratum with single sampling unit.
> What is wrong with it?
>
> After that I did some tests considering a fictitious cluster variable and worked.   I suppose this command works only when the 3 design variables weight strata and cluster are used at the same time.

-- 
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.

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