R help - Oct 2012 - Package survey: Compute standard deviations from complex survey designs

Hello,

svyvar from the survey package computes variances (with standard errors) 
from survey design objects. Is there any way to compute standard 
deviations and their standard errors in a similar manner?

Thanks a lot,
Sebastian

On Tue, Oct 16, 2012 at 10:40 PM, Sebastian Weirich
<sebastian.weirich at iqb.hu-berlin.de> wrote:
> Hello,
>
> svyvar from the survey package computes variances (with standard errors)
> from survey design objects. Is there any way to compute standard deviations
> and their standard errors in a similar manner?
Usually you can do this sort of transformation with svycontrast(), but
it doesn't work on the output of svyvar().  You need to use the delta
method directly.

#compute variances
> vv<-svyvar(~api00+api99,dclus1)
## variance
> coef(vv)	
         api00    api99
api00 11182.82 11516.33
api99 11516.33 12735.21
## variance of variance
> vcov(vv)
        api00   api00   api99   api99
api00 1922144 1920707 1920707 1851400
api00 1920707 1996169 1996169 2004475
api99 1920707 1996169 1996169 2004475
api99 1851400 2004475 2004475 2102736

## standard error is square root of variance
> sqrt(diag(coef(vv)))
   api00    api99
105.7489 112.8504
## delta method for standard error of square root of
variance
>
sqrt(vcov(vv)["api00","api00"]/(4*coef(vv)["api00","api00"]))
[1] 6.555219



  -thomas


-- 
Thomas Lumley
Professor of Biostatistics
University of Auckland