it might be slightly different, but i think the result is very close to a
tsl result (which hasn't been implemented).. could you use this?
mns<-svyby(~api00+api99, ~stype, rclus1, svytotal,covmat=TRUE)
vcov(mns)
On Wed, Oct 15, 2014 at 9:27 AM, Daniela Droguett <
daniela.droguett.leon at gmail.com> wrote:
> Hi,
>
> I would like to apply the vcov function from the survey package for the
> variables api00 and api99 grouped by the stype variable which can assume H,
> M and E categories.
>
> ?From the code in the survey package manual:?
>
> ?data(api)
> dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
> rclus1<-as.svrepdesign(dclus1)
> mns<-svyby(~api00, ~stype, rclus1, svymean,covmat=TRUE)
> vcov(mns)
>
> I have tried the following changes in order to get the variance matrix
> estimation (as part of Taylor Linearization).
>
> > data(api)
> > dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
>
> ?> mns<-svyby(~api00+api99, ~stype, dclus1, svytotal)
> > mns
> stype api00 api99 se.api00 se.api99
> E E 3162561.8 2962356.8 842713.7 796474.0
> H H 293115.0 282283.9 104059.8 101492.9
> M M 534308.7 514982.0 108710.7 105036.6
> > vcov(mns)
> E:api00 H:api00 M:api00 E:api99 H:api99
> M:api99
> E:api00 710166313660 0 0 0 0
> 0
> H:api00 0 10828434454 0 0 0
> 0
> M:api00 0 0 11818006832 0 0
> 0
> E:api99 0 0 0 634370797647 0
> 0
> H:api99 0 0 0 0 10300818294
> 0
> M:api99 0 0 0 0 0
> 11032691751
> Warning message:
> In vcov.svyby(mns) : Only diagonal elements of vcov() available
>
> How to obtain the cross terms in the matrix above?
>
> I have no clue on how to implement that.
>
> Thanks a lot!
>
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>
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