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Re: st: logistic regression complex samples


From   Antonio silva <asilva@inbox.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: logistic regression complex samples
Date   Thu, 8 Dec 2011 19:31:37 -0800

Dear Steve.
It works now!.Thanks for all your help.

And many thanks to everyone who helped me . 
Best regards,
Antonio.

> -----Original Message-----
> From: sjsamuels@gmail.com
> Sent: Thu, 8 Dec 2011 09:26:16 -0500
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: logistic regression complex samples
> 
> Correction, the command for getting -svylogitgof- is "findit svylogitgof"
> 
> Steve
> 
> On Dec 7, 2011, at 10:43 PM, Steve Samuels wrote:
> 
> 
> Thanks for the detailed command output, but you are on the wrong track.
> The error message has nothing to do with leaving a cluster variable (PSU
> or "primary sampling unit") out of the -svyset- command. SAS and Stata
> behave the same in this regard. The proof is that in the -logistic-
> results, the "Number of PSUs" and "Number of obs" are the same.
> 
> We've already given you suggestions and links for fixing the problem
> identified by the error message. There are different solutions, and you
> will have to choose. You have encountered Stata's default behavior when
> there is only one PSU in some strata. I suspect it's intended to force
> the user to make a deliberate choice.
> 
> The most conservative approach (biggest standard errors) would be the
> following:
> 
> *********************************************************************
> svyset [pweight= var_weight], strata(var_strata) singleunit(centered)
> *********************************************************************
> 
> I suggest that you figure out why there are singleton strata, because the
> answer might help you choose a better solution. One possibility is that
> there were more observations in the stratum, but that all but one have
> missing values for an analysis variable.  Another guess is that you have
> a subset of the original survey data, and the subgroup has only one
> member in some strata.  (If you have subset the data, you should use a
> -subpop- option in your -svy: logistic- model.) Still another possibility
> is that some observations were marked in advance to be in the sample; in
> other words they are "certainty" units; and each was given its own
> stratum. This is one of the possibilities for the -singleunit()- option
> of the -svyset- command.
> 
> The contributed command you refer to (the FAQ ask that you give exact
> references) is -svylogitgof-. You can install it by typing "find
> svylogitgof" and going to the first listed "package".
> 
> 
> Steve
> sjsamuels@gmail.com
> 
> 
> 
> 
> 
> 
> 
> On Dec 7, 2011, at 8:01 PM, Antonio silva 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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