Hello Thomas,
I use both svymean (with the expanded sample = people), and svyratio
(voting unit level), using the same design:
design <-svydesign(id=~station + unit, fpc=~probstation+probunits,
data=sample, pps="brewer")
I got different results using the same sample:
svyratio (voting unit)
On Fri, Oct 12, 2012 at 6:56 AM, Sebastián Daza
wrote:
> Hello,
>
> I have got a cluster sample using an election dataset where I already
> had the final results of a county-specific election. I am trying to
> figure out what would be the best sampling design for my data.
>
> The structure of the
Hello,
I have got a cluster sample using an election dataset where I already
had the final results of a county-specific election. I am trying to
figure out what would be the best sampling design for my data.
The structure of the dataset is:
1) polling station (in general schools where people vo
On Thu, 18 Feb 2010, Richard Valliant wrote:
Should the svyby function be able to work with svyquantile? I get the
error below ...
It works, but you need to either specify ci=TRUE or keep.var=FALSE. The
problem is that svyquantile() by default does not produce standard errors.
svyby(~api0
Should the svyby function be able to work with svyquantile? I get the
error below ...
data(api)
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
svyby(~api00,
design=dclus1,
by = ~stype,
quantiles=c(.25,.5,.75),
FUN=svyquantile,
na.
Good afternoon!
1 I have a bit of a problem with the Survey package, but one that is more
theoretical than practical. If for example on wishes to use some additional
information which comprises of 4 variables with 7, 5,5 and 5 categories
(resulting in 875 post-strata if the whole crossin
6 matches
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