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Re: st: logistic regression complex samples


From   Stas Kolenikov <skolenik@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: logistic regression complex samples
Date   Wed, 7 Dec 2011 20:42:42 -0600

-svydes- command can give you an easy indication if a singleton PSU
(the only PSU in a stratum) is an issue. It may also be that a wicked
combination of regressors (e.g., one of the levels is only present
once in the data) produces this sort of a problem: for whatever
reason, the variance-covariance matrix of the estimates came out to be
degenerate, and -svy- produced a default diagnostics of the singleton
PSU.

On Wed, Dec 7, 2011 at 7:01 PM, Antonio silva <asilva@inbox.com> wrote:
> Thanks for the replies. I can run a model using  SAS surveylogistic without  the cluster variable but I have had  difficulties to do the same with Stata version 11. I am a beginner in Stata programming.My final goal is to calculate the Archer  and  Lemeshow  (A-L;  2006) goodness of fit test (with estat gof command) that is not available in SAS. To do that I have to  run correctly the logistic regression model (with only weight and strata without cluster) in Stata. I hope someone can help with the Stata code.
> Consider the following  code (ex. with 2 categorical covariates)  that have been used and the output .
>
> svyset [pweight= var_weight], strata(var_strata)
>
>
> .  xi: svy: logistic outcome i.covar1  i.covar2_3cat
>
>
> i.covar1            _Icovar1_1-2          (naturally coded; _Icovar1_1 omitted)
> i.covar2_3cat    _Icovar2_3_1-3     (naturally coded; _Icovar2_3_1 omitted)
> (running logistic on estimation sample)
>
> Survey: Logistic regression
>
> Number of strata   =         9                  Number of obs      =       398
> Number of PSUs     =       398                  Population size    = 4361.1088
>                                                Design df          =       389
>                                                F(   0,    389)    =         .
>                                                Prob > F           =         .
>
> ------------------------------------------------------------------------------
>             |             Linearized
>      outcome | Odds Ratio   Std. Err.      t    P>|t|     [95% Conf. Interval]
> -------------+----------------------------------------------------------------
>    _Icovar1_2 |   1.926984          .        .       .            .           .
> _Icovar2_~2 |   .2875105          .        .       .            .           .
> _Icovar2_~3 |   .1978389          .        .       .            .           .
> ------------------------------------------------------------------------------
> Note: missing standard errors because of stratum with single sampling unit.
>
> Thanks,
> Antonio.
>> -----Original Message-----
>> From: skolenik@gmail.com
>> Sent: Wed, 7 Dec 2011 11:18:37 -0600
>> To: statalist@hsphsun2.harvard.edu
>> Subject: Re: st: logistic regression complex samples
>>
>> 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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>> *   http://www.ats.ucla.edu/stat/stata/
>
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-- 
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


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