svycontrast | R Documentation |
Computes linear or nonlinear contrasts of estimates produced by survey
functions (or any object with coef
and vcov
methods).
svycontrast(stat, contrasts, add=FALSE, ...)
stat |
object of class |
contrasts |
A vector or list of vectors of coefficients, or a call or list of calls |
add |
keep all the coefficients of the input in the output? |
... |
For future expansion |
If contrasts
is a list, the element names are used as
names for the returned statistics.
If an element of contrasts
is shorter than coef(stat)
and has names, the
names are used to match up the vectors and the remaining elements of
contrasts
are assumed to be zero. If the names are not legal
variable names (eg 0.1
) they must be quoted (eg "0.1"
)
If contrasts
is a "call"
or list of "call"s
, and
stat
is a svrepstat
object including replicates, the
replicates are transformed and used to compute the variance. If
stat
is a svystat
object or a svrepstat
object
without replicates, the delta-method is used to compute variances, and
the calls must use only functions that deriv
knows how
to differentiate. If the names are not legal variable names they must
be quoted with backticks (eg `0.1`
).
If stats
is a svyvar
object, the estimates are elements of a matrix and the names are the row and column names pasted together with a colon.
Object of class svrepstat
or svystat
or svyvar
regTermTest
, svyglm
data(api)
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
a <- svytotal(~api00+enroll+api99, dclus1)
svycontrast(a, list(avg=c(0.5,0,0.5), diff=c(1,0,-1)))
## if contrast vectors have names, zeroes may be omitted
svycontrast(a, list(avg=c(api00=0.5,api99=0.5), diff=c(api00=1,api99=-1)))
## nonlinear contrasts
svycontrast(a, quote(api00/api99))
svyratio(~api00, ~api99, dclus1)
## Example: standardised skewness coefficient
moments<-svymean(~I(api00^3)+I(api00^2)+I(api00), dclus1)
svycontrast(moments,
quote((`I(api00^3)`-3*`I(api00^2)`*`I(api00)`+ 3*`I(api00)`*`I(api00)`^2-`I(api00)`^3)/
(`I(api00^2)`-`I(api00)`^2)^1.5))
## Example: geometric means
## using delta method
meanlogs <- svymean(~log(api00)+log(api99), dclus1)
svycontrast(meanlogs,
list(api00=quote(exp(`log(api00)`)), api99=quote(exp(`log(api99)`))))
## using delta method
rclus1<-as.svrepdesign(dclus1)
meanlogs <- svymean(~log(api00)+log(api99), rclus1)
svycontrast(meanlogs,
list(api00=quote(exp(`log(api00)`)),
api99=quote(exp(`log(api99)`))))
## why is add=TRUE useful?
(totals<-svyby(~enroll,~stype,design=dclus1,svytotal,covmat=TRUE))
totals1<-svycontrast(totals, list(total=c(1,1,1)), add=TRUE)
svycontrast(totals1, list(quote(E/total), quote(H/total), quote(M/total)))
totals2<-svycontrast(totals, list(total=quote(E+H+M)), add=TRUE)
all.equal(as.matrix(totals1),as.matrix(totals2))
## more complicated svyby
means <- svyby(~api00+api99, ~stype+sch.wide, design=dclus1, svymean,covmat=TRUE)
svycontrast(means, quote(`E.No:api00`-`E.No:api99`))
svycontrast(means, quote(`E.No:api00`/`E.No:api99`))
## transforming replicates
meanlogs_r <- svymean(~log(api00)+log(api99), rclus1, return.replicates=TRUE)
svycontrast(meanlogs_r,
list(api00=quote(exp(`log(api00)`)), api99=quote(exp(`log(api99)`))))
## converting covariances to correlations
vmat <-svyvar(~api00+ell,dclus1)
print(vmat,cov=TRUE)
cov2cor(as.matrix(vmat))[1,2]
svycontrast(vmat, quote(`api00:ell`/sqrt(`api00:api00`*`ell:ell`)))
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