Home
last modified time | relevance | path

Searched +refs:svyratio +refs:survey +refs:design (Results 1 – 25 of 34) sorted by relevance

12

/dports/math/R-cran-survey/survey/
H A DNAMESPACE21 S3method(svyloglin,survey.design)
76 S3method(svymean, survey.design)
92 S3method(svyratio, survey.design)
93 S3method(svyratio, svyrep.design)
94 S3method(svyratio, survey.design2)
100 S3method(svyvar, survey.design)
124 S3method(svyglm,survey.design)
233 S3method(svykm, survey.design)
290 S3method(print, survey.design)
313 S3method(dim,survey.design)
[all …]
H A DINDEX1 svydesign Specify a survey design
4 as.svrepdesign Compute replication weights for a design
6 subset.survey.design Subset of survey
7 update.survey.design Add variables to a survey design
8 postStratify Post-stratify a survey design
9 rake Rake a survey design
17 svycoplot Conditioning plots for survey data
18 svyqqplot Quantile-quantile plots for survey data
30 deff extract design effect
46 svyratio
[all …]
/dports/math/R-cran-survey/survey/man/
H A Dsvyratio.Rd5 \alias{svyratio.svyrep.design}
6 \alias{svyratio.survey.design}
7 \alias{svyratio.survey.design2}
22 \method{svyratio}{survey.design2}(numerator=formula, denominator,
25 \method{svyratio}{svyrep.design}(numerator=formula, denominator, design,
40 \item{design}{survey design object}
91 ## survey design objects
106 svyratio(~alive, ~arrests, design=scddes)
107 svyratio(~alive, ~arrests, design=scdnofpc)
108 svyratio(~alive, ~arrests, design=scd2brr)
[all …]
H A Das.svrepdesign.Rd7 \title{Convert a survey design to use replicate weights}
9 Creates a replicate-weights survey design object from a traditional
10 strata/cluster survey design object. \code{JK1} and \code{JKn} are
24 mse=getOption("survey.replicates.mse"))
28 mse=getOption("survey.replicates.mse"))
32 \item{design}{Object of class \code{survey.design} or \code{svyimputationList}}
85 svyratio(~alive, ~arrests, design=scd2brr)
86 svyratio(~alive, ~arrests, design=scd2brr1)
87 svyratio(~alive, ~arrests, design=scd2fay)
88 svyratio(~alive, ~arrests, design=scd2jkn)
[all …]
H A Dsurveysummary.Rd3 \alias{svymean.survey.design}
9 \alias{svytotal.survey.design}
13 \alias{svyvar.survey.design}
19 \alias{cv.svyratio}
36 \method{svymean}{survey.design}(x, design, na.rm=FALSE,deff=FALSE,influence=FALSE,...)
41 \method{svyvar}{survey.design}(x, design, na.rm=FALSE,...)
44 \method{svytotal}{survey.design}(x, design, na.rm=FALSE,deff=FALSE,influence=FALSE,...)
62 \item{design}{\code{survey.design} or \code{svyrep.design} object}
181 svyratio(~api.stu, ~enroll, dclus1)
200 svyratio(~api.stu, ~enroll, jkstrat)
[all …]
H A Dscd.Rd28 ## survey design objects
45 svyratio(~alive, ~arrests, design=scddes)
46 svyratio(~alive, ~arrests, design=scdnofpc)
47 svyratio(~alive, ~arrests, design=scd2brr)
48 svyratio(~alive, ~arrests, design=scd2boot)
49 svyratio(~alive, ~arrests, design=scdrep)
52 summary(svyglm(cbind(alive,arrests-alive)~1, family=quasibinomial, design=scdnofpc))
53 summary(svyglm(cbind(alive,arrests-alive)~1, family=quasibinomial, design=scdrep))
55 # Because no sampling weights are given, can't compute design effects
H A Dsvyby.Rd10 \alias{svyby.survey.design2}
14 Compute survey statistics on subsets of a survey defined by factors.
17 svyby(formula, by ,design,...)
22 multicore=getOption("survey.multicore"))
23 \method{svyby}{survey.design2}(formula, by, design, FUN, ..., deff=FALSE,keep.var = TRUE,
26 na.rm.by=FALSE, na.rm.all=FALSE, multicore=getOption("survey.multicore"))
42 \item{FUN}{A function taking a formula and survey design object as its
119 \code{\link{update.survey.design}} to add variables to the design
185 svyby(~api.stu, by=~stype, denominator=~enroll, design=dclus1, svyratio)
187 ratios<-svyby(~api.stu, by=~stype, denominator=~enroll, design=dclus1, svyratio,covmat=TRUE)
[all …]
H A Dsvrepdesign.Rd6 \alias{[.svyrep.design}
7 \alias{image.svyrep.design}
8 \alias{print.svyrep.design}
10 \alias{summary.svyrep.design}
13 \title{Specify survey design with replicate weights}
17 data structure for such a survey.
26 mse=getOption("survey.replicates.mse"),...)
57 \item{x}{survey design with replicate weights}
121 \code{RSQLite} for SQLite). The survey design
133 \code{\link{as.svrepdesign}} on a \code{survey.design} object, or see
[all …]
/dports/math/R-cran-survey/survey/tests/testoutput/
H A Dbycovmat.R2 library(survey)
8 a<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
10 b<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
20 rat <- svyratio(~ell+mobility, ~mobility+meals, dclus1,covmat=TRUE)
31 rat <- svyratio(~ell+mobility, ~mobility+meals, rclus1,covmat=TRUE)
39 stopifnot(all(abs(survey:::svrVar(con$replicates, rclus1$scale,rclus1$rscales,mse=rclus1$mse, coef=…
45 a<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
47 b<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
57 rat <- svyratio(~ell+mobility, ~mobility+meals, dclus1,covmat=TRUE)
68 rat <- svyratio(~ell+mobility, ~mobility+meals, rclus1,covmat=TRUE)
[all …]
H A Dbycovmat.Rout.save19 > library(survey)
21 Attaching package: 'survey'
28 > options(survey.replicates.mse=TRUE)
32 > a<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
34 > b<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
44 > rat <- svyratio(~ell+mobility, ~mobility+meals, dclus1,covmat=TRUE)
55 > rat <- svyratio(~ell+mobility, ~mobility+meals, rclus1,covmat=TRUE)
65 > options(survey.replicates.mse=FALSE)
69 > a<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
71 > b<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
[all …]
H A DDBIcheck.Rout.save21 > library(survey)
26 Attaching package: ‘survey’
39 + data="apiclus1",dbtype="SQLite", dbname=system.file("api.db",package="survey"))
48 > r<-svyratio(~api_stu, ~enroll, design=dclus1)
49 > r.db<-svyratio(~api_stu, ~enroll, design=dbclus1)
55 > b<-svyby(~api99+api00,~stype, design=dclus1, svymean, deff=TRUE)
56 > b.db<-svyby(~api99+api00,~stype, design=dbclus1,svymean, deff=TRUE)
64 > l<-svyglm(api00~api99+mobility, design=dclus1)
65 > l.db<-svyglm(api00~api99+mobility, design=dbclus1)
94 DB-backed replicate weight design
[all …]
H A DDBIcheck.R2 library(survey)
17 r<-svyratio(~api_stu, ~enroll, design=dclus1)
18 r.db<-svyratio(~api_stu, ~enroll, design=dbclus1)
22 b<-svyby(~api99+api00,~stype, design=dclus1, svymean, deff=TRUE)
23 b.db<-svyby(~api99+api00,~stype, design=dbclus1,svymean, deff=TRUE)
28 l<-svyglm(api00~api99+mobility, design=dclus1)
29 l.db<-svyglm(api00~api99+mobility, design=dbclus1)
/dports/math/R-cran-survey/survey/tests/
H A Dbycovmat.R2 library(survey)
8 a<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
10 b<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
20 rat <- svyratio(~ell+mobility, ~mobility+meals, dclus1,covmat=TRUE)
31 rat <- svyratio(~ell+mobility, ~mobility+meals, rclus1,covmat=TRUE)
39 stopifnot(all(abs(survey:::svrVar(con$replicates, rclus1$scale,rclus1$rscales,mse=rclus1$mse, coef=…
45 a<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
47 b<-svyby(~api00+api99, ~comp.imp+sch.wide,design=rclus1,svymean,
57 rat <- svyratio(~ell+mobility, ~mobility+meals, dclus1,covmat=TRUE)
68 rat <- svyratio(~ell+mobility, ~mobility+meals, rclus1,covmat=TRUE)
[all …]
H A Ddomain.Rout.save26 > library(survey)
28 Attaching package: 'survey'
37 > (m1<-svymean(~x,design=dsub))
46 > m3<-svyglm(x~I(x>4)+0,design=dfpc)
50 svyglm(formula = x ~ I(x > 4) + 0, design = dfpc)
52 Survey design:
67 > (m4<-svyratio(~I(x*(x>4)),~as.numeric(x>4), dfpc))
68 Ratio estimator: svyratio.survey.design2(~I(x * (x > 4)), ~as.numeric(x > 4),
84 > m3<- svyratio(~I(enroll*(comp.imp=="Yes")), ~as.numeric(comp.imp=="Yes"), dstrat)
92 1 - level Cluster Sampling design
[all …]
H A DDBIcheck.R2 library(survey)
17 r<-svyratio(~api_stu, ~enroll, design=dclus1)
18 r.db<-svyratio(~api_stu, ~enroll, design=dbclus1)
22 b<-svyby(~api99+api00,~stype, design=dclus1, svymean, deff=TRUE)
23 b.db<-svyby(~api99+api00,~stype, design=dbclus1,svymean, deff=TRUE)
28 l<-svyglm(api00~api99+mobility, design=dclus1)
29 l.db<-svyglm(api00~api99+mobility, design=dbclus1)
H A Ddomain.R9 library(survey)
13 (m1<-svymean(~x,design=dsub))
16 (m2<-svyby(~x,~I(x>4),design=dfpc, svymean,keep.var=TRUE))
17 m3<-svyglm(x~I(x>4)+0,design=dfpc)
19 (m4<-svyratio(~I(x*(x>4)),~as.numeric(x>4), dfpc))
28 m3<- svyratio(~I(enroll*(comp.imp=="Yes")), ~as.numeric(comp.imp=="Yes"), dstrat)
38 m3<-svyratio(~I(api00*(comp.imp=="Yes")), ~as.numeric(comp.imp=="Yes"), dclus1g3)
49 m3<-svyratio(~I(api00*(comp.imp=="Yes")), ~as.numeric(comp.imp=="Yes"), dclus1r)
110 reg<-svyglm(y~I(y<4), design=des.rei2)
H A Dregpredict.R1 library(survey)
10 api.reg <- svyglm(api.stu~enroll, design=dstrat)
23 api.reg2 <- svyglm(api.stu~enroll-1, design=dstrat,
29 e <- predict(svyratio(~api.stu, ~enroll, dstrat),total=pop$enroll)
H A Dregpredict.Rout.save18 > library(survey)
20 Attaching package: 'survey'
34 > api.reg <- svyglm(api.stu~enroll, design=dstrat)
49 > api.reg2 <- svyglm(api.stu~enroll-1, design=dstrat,
55 > e <- predict(svyratio(~api.stu, ~enroll, dstrat),total=pop$enroll)
/dports/math/R-cran-survey/survey/inst/doc/
H A Ddomain.Rnw20 survey design objects automatically do the necessary adjustments, but
30 library(survey)
34 svymean(~x,design=dsub)
37 The \texttt{subset} function constructs a survey design object with
42 svyby(~x,~I(x>4),design=dfpc, svymean)
50 summary(svyglm(x~I(x>4)+0,design=dfpc))
58 svyratio(~I(x*(x>4)),~as.numeric(x>4), dfpc)
62 for observations not in the domain. For most survey design objects
83 svyratio(~I(api00*(comp.imp=="Yes")), ~as.numeric(comp.imp=="Yes"), gclus1)
93 svyratio(~I(y1*(y1>40)),~as.numeric(y1>40),dmu284)
[all …]
H A Dsurvey.R6 library(survey)
24 svyratio(~api.stu,~enroll, dclus1)
30 svyratio(~api.stu, ~enroll, design=subset(dclus1, stype=="H"))
43 svyby(~ell+meals, ~stype, design=dclus1, svymean)
49 regmodel <- svyglm(api00~ell+meals,design=dclus1)
50 logitmodel <- svyglm(I(sch.wide=="Yes")~ell+meals, design=dclus1, family=quasibinomial())
68 svyratio(~api.stu,~enroll, gclus1)
H A Dsurvey.Rnw3 %\VignetteIndexEntry{A survey analysis example}
6 \title{A survey analysis example}
11 This document provides a simple example analysis of a survey data set,
27 library(survey)
42 design object containing the data.
48 svyratio(~api.stu,~enroll, dclus1)
56 svyratio(~api.stu, ~enroll, design=subset(dclus1, stype=="H"))
74 svyby(~ell+meals, ~stype, design=dclus1, svymean)
80 regmodel <- svyglm(api00~ell+meals,design=dclus1)
81 logitmodel <- svyglm(I(sch.wide=="Yes")~ell+meals, design=dclus1, family=quasibinomial())
[all …]
H A Ddomain.R6 library(survey)
10 svymean(~x,design=dsub)
16 svyby(~x,~I(x>4),design=dfpc, svymean)
22 summary(svyglm(x~I(x>4)+0,design=dfpc))
28 svyratio(~I(x*(x>4)),~as.numeric(x>4), dfpc)
40 svyratio(~I(api00*(comp.imp=="Yes")), ~as.numeric(comp.imp=="Yes"), gclus1)
51 svyratio(~I(y1*(y1>40)),~as.numeric(y1>40),dmu284)
64 svyratio(~I(rel*as.numeric(age>36)), ~as.numeric(age>36), dccs8)
/dports/math/R-cran-survey/survey/vignettes/
H A Ddomain.Rnw20 survey design objects automatically do the necessary adjustments, but
30 library(survey)
34 svymean(~x,design=dsub)
37 The \texttt{subset} function constructs a survey design object with
42 svyby(~x,~I(x>4),design=dfpc, svymean)
50 summary(svyglm(x~I(x>4)+0,design=dfpc))
58 svyratio(~I(x*(x>4)),~as.numeric(x>4), dfpc)
62 for observations not in the domain. For most survey design objects
83 svyratio(~I(api00*(comp.imp=="Yes")), ~as.numeric(comp.imp=="Yes"), gclus1)
93 svyratio(~I(y1*(y1>40)),~as.numeric(y1>40),dmu284)
[all …]
H A Dsurvey.Rnw3 %\VignetteIndexEntry{A survey analysis example}
6 \title{A survey analysis example}
11 This document provides a simple example analysis of a survey data set,
27 library(survey)
42 design object containing the data.
48 svyratio(~api.stu,~enroll, dclus1)
56 svyratio(~api.stu, ~enroll, design=subset(dclus1, stype=="H"))
74 svyby(~ell+meals, ~stype, design=dclus1, svymean)
80 regmodel <- svyglm(api00~ell+meals,design=dclus1)
81 logitmodel <- svyglm(I(sch.wide=="Yes")~ell+meals, design=dclus1, family=quasibinomial())
[all …]
/dports/math/R-cran-survey/survey/inst/
H A DNEWS78 regTermTest(,method="LRT") didn't work if the survey design object and model were
155 3.36 Add withPV.survey.design for plausible-value analyses (needs mitools >=2.4)
545 3.21-3 svyratio() can now estimate design effects (for Scott Kostyshak)
943 3.6-2 covmat=TRUE option for svyratio.
1015 svyratio() for two-phase designs.
1064 svyratio handles missing data.
1165 cv.svyratio was inverted.
1167 rake() on survey design objects was accumulating cruft in the
1199 2.9 Added full multistage sampling, involving a redesign of the survey.design
1204 about old-style survey objects. If you must create old-style survey
[all …]

12