Hi R-users!
I have a problem with the survey package and i would be very grateful if you
can help me.
A short example:
stratum id weight nh Nh y sex
1 1 3 5 15 23 1
1 2 3 5 15 25 1
1 3 3 5 15 27 2
1 4 3 5 15 21 2
1 5 3 5 15 22 1
2 6 4 3 12 33 1
2 7 4 3 12 27 1
2 8 4 3 12 29 2
where nh is size of sample stratum and Nh the corresponding population value,
and y is metric variable.
Now if i let
design <- svydesign( id=~1, data=age, strata=~stratum, fpc=~Nh)
then weights(design) gives me 3,3,3,3,3,4,4,4.
If i then let
x<- postStratify( design, strata=~sex, data.frame(sex=c("1","2"),
freq=c(10,15)))
the weights become
1 2 3 4 5 6
7 8
2.17 2.17 5.35 5.35 2.17 1.73 1.73
4.28
If i define
design <- svydesign( id=~1, data=age )
x<- postStratify( design, strata=~sex, data.frame(sex=c("1","2"),
freq=c(10,15)))
weights become 2 2 5 5 2 2 2 5
The question: does poststratify recognize that i have already stratified in the
first design by stratum and then it post stratifies by sex? and why is that?
(because i don't have the full joint distribution, the sex*stratum crossing, in
order to apply correctly the post stratify function)
I see that Mr Lumley uses the postStratify function when the design does not
include strata (eg from ?poststratify:
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
rclus1<-as.svrepdesign(dclus1)
rclus1p<-postStratify(rclus1, ~stype, pop.types)
and i use
design <- svydesign( id=~1, data=age, strata=~stratum, fpc=~Nh)
x<- postStratify( design, strata=~sex, data.frame(sex=c("1","2"),
freq=c(10,15)))
which has a first strata (stratum from svydesign) and a second strata(sex, from
poststratify)
Is it correct to use the functions as use them or am i doing something wrong?
Thank you !
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