I achive something diferent, I replicated the t value, the std. error and
the hypothesis test but differents betas.
But, you are right, the thing is, I detach the dataset, but even with it, I
couldn't.

I going to describe all because perhaps I omitted something important.
I have this vector for the weights "wst7". My dataset it's a panel survey
with 103 observations missing. "wst7" is the weight and the non response
adjustment factor, with data only for 248 observations.

> class(wst7)
[1] "numeric"
> summary(wst7)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's
   0.00   10.26   13.52   21.33   25.85  146.00     103

If I use "wst7" to create de svydesign this appear:

> test <- svydesign(id=~1,weights=~wst7)
Error in function (object, ...)  : missing values in `weights'

So, I create a vector without NAs (now with the dataset detach).

peso<-na.omit(matrix(data$wst7))

Then

test <- svydesign(id=~fullid,weights=~peso)

(fullid is the identification for each observation, I also used "1", or
whatever you whant there)

Then

logit <- svyglm(bach ~ job2 + mujer + egp4 + programa + delay + mdeo + str
+
                  evprivate, family=binomial(link="logit"), design=test,
data=data)

This appear
Error in svyglm.survey.design(bach ~ job2 + mujer + egp4 + programa +  :
  all variables must be in design= argument

Even if I try to use svy as svymean

svymean(data$mujer, design=test)
        mean     SE
[1,] 0.78843 0.0479
Warning messages:
1: In x * pweights :
  longer object length is not a multiple of shorter object length
2: In x * pweights :
  longer object length is not a multiple of shorter object length

When the mean for "mujer" is

. svy: mean mujer
(running mean on estimation sample)

Survey: Mean estimation

Number of strata =       1          Number of obs =     248
Number of PSUs   =     248          Population size = 5290.16
Design df =     247

Linearized
                   Mean   Std. Err.     [95% Conf. Interval]
mujer    .5551581   .0410122      .4743798 .6359363

So, I thing that the problem is in the survey design...



On Tue, Nov 27, 2012 at 11:49 PM, David Winsemius <dwinsemius@comcast.net>wrote:

>
> On Nov 27, 2012, at 2:31 PM, Pablo Menese wrote:
>
>  Sorry, it send it alone...
>>
>> When I use it:
>>
>> logit <- glm(bach ~ egp4 + programa, weight=wst7,
>> family=quasibinomial(link"**logit"))
>>
>> I reach the same betas that in STATA, but the hypothesis test, the t
>> value, and the std. error is different.
>>
>
> As might be expected if one (Stata) were a weighted analysis and the (R)
> other is using a different interpretation of "weights".
>
>
>> I think that the solution can't be so far from this...
>>
>
> If so, then you will be the one to achieve it. You have offered no data in
> either the original question for which you have omitted context, and the
> code in this posting  is obviously incorrect. Furthermore you started with
> a `svyglm` question and this code only attempts to use `glm`.
>
>
> --
>
> David Winsemius, MD
> Alameda, CA, USA
>
>

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