Creates a replicate-weights survey design object from a traditional
strata/cluster survey design object. JK1
and JKn
are
jackknife methods, BRR
is Balanced Repeated Replicates and
Fay
is Fay's modification of this, bootstrap
is Canty
and Davison's bootstrap, subbootstrap
is Rao and Wu's
\((n-1)\) bootstrap, and mrbbootstrap
is Preston's multistage rescaled bootstrap.
as.svrepdesign(design, type=c("auto", "JK1", "JKn", "BRR", "bootstrap",
"subbootstrap","mrbbootstrap","Fay"),
fay.rho = 0, fpc=NULL,fpctype=NULL,..., compress=TRUE,
mse=getOption("survey.replicates.mse"))
Object of class survey.design
Type of replicate weights. "auto"
uses JKn for
stratified, JK1 for unstratified designs
Tuning parameter for Fay's variance method
Passed to jk1weights
, jknweights
,
brrweights
, bootweights
, subbootweights
, or mrbweights
.
Use a compressed representation of the replicate weights matrix.
if TRUE
, compute variances from sums of squares around
the point estimate, rather than the mean of the replicates
Object of class svyrep.design
.
Canty AJ, Davison AC. (1999) Resampling-based variance estimation for labour force surveys. The Statistician 48:379-391
Judkins, D. (1990), "Fay's Method for Variance Estimation," Journal of Official Statistics, 6, 223-239.
Preston J. (2009) Rescaled bootstrap for stratified multistage sampling. Survey Methodology 35(2) 227-234
Rao JNK, Wu CFJ. Bootstrap inference for sample surveys. Proc Section on Survey Research Methodology. 1993 (866--871)
brrweights
, svydesign
,
svrepdesign
, bootweights
, subbootweights
, mrbweights
# NOT RUN { data(scd) scddes<-svydesign(data=scd, prob=~1, id=~ambulance, strata=~ESA, nest=TRUE, fpc=rep(5,6)) scdnofpc<-svydesign(data=scd, prob=~1, id=~ambulance, strata=~ESA, nest=TRUE) # convert to BRR replicate weights scd2brr <- as.svrepdesign(scdnofpc, type="BRR") scd2fay <- as.svrepdesign(scdnofpc, type="Fay",fay.rho=0.3) # convert to JKn weights scd2jkn <- as.svrepdesign(scdnofpc, type="JKn") # convert to JKn weights with finite population correction scd2jknf <- as.svrepdesign(scddes, type="JKn") ## with user-supplied hadamard matrix scd2brr1 <- as.svrepdesign(scdnofpc, type="BRR", hadamard.matrix=paley(11)) svyratio(~alive, ~arrests, design=scd2brr) svyratio(~alive, ~arrests, design=scd2brr1) svyratio(~alive, ~arrests, design=scd2fay) svyratio(~alive, ~arrests, design=scd2jkn) svyratio(~alive, ~arrests, design=scd2jknf) data(api) ## one-stage cluster sample dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) ## convert to JK1 jackknife rclus1<-as.svrepdesign(dclus1) ## convert to bootstrap bclus1<-as.svrepdesign(dclus1,type="bootstrap", replicates=100) svymean(~api00, dclus1) svytotal(~enroll, dclus1) svymean(~api00, rclus1) svytotal(~enroll, rclus1) svymean(~api00, bclus1) svytotal(~enroll, bclus1) dclus2<-svydesign(id = ~dnum + snum, fpc = ~fpc1 + fpc2, data = apiclus2) mrbclus2<-as.svrepdesign(dclus2, type="mrb",replicates=100) svytotal(~api00+stype, dclus2) svytotal(~api00+stype, mrbclus2) # }
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