Package survey: Compute standard deviations from complex survey designs

On Tue, Oct 16, 2012 at 10:40 PM, Sebastian Weirich

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