[R] Question on survey package

[Thomas Lumley]

On Thu, 2 Sep 2004, Richard Valliant wrote:

> Is there a way to use one of the functions in the survey package to get
> a table of estimated percentages (or proportions) and the standard error
> for each?  For example, suppose that AGECODE AND SEX are two factors
> with 5 and 2 levels.
>
> The 5x2 AGECODE x SEX table would have the estimated percentage of
> persons in each cell,
>

The computations can be done easily enough with svymean or svrepmean, but
the layout isn't quite what you want

Example:

library(survey)
data(api)
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)

> svymean(~interaction(stype,comp.imp),design=dclus1)
                                      mean     SE
interaction(stype, comp.imp)E.No  0.174863 0.0260
interaction(stype, comp.imp)H.No  0.038251 0.0161
interaction(stype, comp.imp)M.No  0.060109 0.0246
interaction(stype, comp.imp)E.Yes 0.612022 0.0417
interaction(stype, comp.imp)H.Yes 0.038251 0.0161
interaction(stype, comp.imp)M.Yes 0.076503 0.0217


Turning this into a 3x2 table with a mean and SE in each cell would take a
bit of work since R doesn't have a very general table layout system.

One approach is

ftable.svystat<-function(x,rownames){

    m<-cbind(coef(x),sqrt(diag(vcov(x))))
    if (is.null(rownames))
        return(as.table(m))

    rowdim<-sapply(rownames,length)

    mm<-array(m,dim=c(rowdim,NCOL(m)),
             dimnames=c(as.list(rownames),
             list(c("coef","SE"))))


    ftable(mm,row.vars=length(rowdim)+0:1)

}

which gives

a <- svymean(~interaction(stype,comp.imp),design=dclus1)
b <- ftable(a,list(c("E","H","M"),c("No","Yes")))

round(b*100,1)
             E    H    M

No  coef  17.5  3.8  6.0
    SE     2.6  1.6  2.5
Yes coef  61.2  3.8  7.7
    SE     4.2  1.6  2.2


or with named dimnames

> b<-ftable(a,list(stype=c("E","H","M"),comp.imp=c("No","Yes")))
> round(b*100,1)
              stype    E    H    M
comp.imp
No       coef       17.5  3.8  6.0
         SE          2.6  1.6  2.5
Yes      coef       61.2  3.8  7.7
         SE          4.2  1.6  2.2



	-thomas