R Under development (unstable) (2024-03-08 r86070 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(survey)
Loading required package: grid
Loading required package: Matrix
Loading required package: survival

Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

> options(survey.replicates.mse=TRUE)
> example(api)

api> library(survey)

api> data(api)

api> mean(apipop$api00)
[1] 664.7126

api> sum(apipop$enroll, na.rm=TRUE)
[1] 3811472

api> #stratified sample
api> dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)

api> summary(dstrat)
Stratified Independent Sampling design
dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)
Probabilities:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.02262 0.02262 0.03587 0.04014 0.05339 0.06623 
Stratum Sizes: 
             E  H  M
obs        100 50 50
design.PSU 100 50 50
actual.PSU 100 50 50
Population stratum sizes (PSUs): 
   E    H    M 
4421  755 1018 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "pw"       "fpc"     

api> svymean(~api00, dstrat)
        mean     SE
api00 662.29 9.4089

api> svytotal(~enroll, dstrat, na.rm=TRUE)
         total     SE
enroll 3687178 114642

api> # one-stage cluster sample
api> dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)

api> summary(dclus1)
1 - level Cluster Sampling design
With (15) clusters.
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
Probabilities:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.02954 0.02954 0.02954 0.02954 0.02954 0.02954 
Population size (PSUs): 757 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "fpc"      "pw"      

api> svymean(~api00, dclus1)
        mean     SE
api00 644.17 23.542

api> svytotal(~enroll, dclus1, na.rm=TRUE)
         total     SE
enroll 3404940 932235

api> # two-stage cluster sample
api> dclus2<-svydesign(id=~dnum+snum, fpc=~fpc1+fpc2, data=apiclus2)

api> summary(dclus2)
2 - level Cluster Sampling design
With (40, 126) clusters.
dclus2<-svydesign(id=~dnum+snum, fpc=~fpc1+fpc2, data=apiclus2)
Probabilities:
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
0.003669 0.037743 0.052840 0.042390 0.052840 0.052840 
Population size (PSUs): 757 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "pw"       "fpc1"     "fpc2"    

api> svymean(~api00, dclus2)
        mean     SE
api00 670.81 30.099

api> svytotal(~enroll, dclus2, na.rm=TRUE)
         total     SE
enroll 2639273 799638

api> # two-stage `with replacement'
api> dclus2wr<-svydesign(id=~dnum+snum, weights=~pw, data=apiclus2)

api> summary(dclus2wr)
2 - level Cluster Sampling design (with replacement)
With (40, 126) clusters.
dclus2wr<-svydesign(id=~dnum+snum, weights=~pw, data=apiclus2)
Probabilities:
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
0.003669 0.037743 0.052840 0.042390 0.052840 0.052840 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "pw"       "fpc1"     "fpc2"    

api> svymean(~api00, dclus2wr)
        mean     SE
api00 670.81 30.712

api> svytotal(~enroll, dclus2wr, na.rm=TRUE)
         total     SE
enroll 2639273 820261

api> # convert to replicate weights
api> rclus1<-as.svrepdesign(dclus1)

api> summary(rclus1)
Call: as.svrepdesign.default(dclus1)
Unstratified cluster jacknife (JK1) with 15 replicates and MSE variances.
Variables: 
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "fpc"      "pw"      

api> svymean(~api00, rclus1)
        mean     SE
api00 644.17 26.335

api> svytotal(~enroll, rclus1, na.rm=TRUE)
         total     SE
enroll 3404940 932235

api> # post-stratify on school type
api> pop.types<-xtabs(~stype, data=apipop)

api> rclus1p<-postStratify(rclus1, ~stype, pop.types)

api> dclus1p<-postStratify(dclus1, ~stype, pop.types)

api> summary(dclus1p)
1 - level Cluster Sampling design
With (15) clusters.
dclus1p<-postStratify(dclus1, ~stype, pop.types)
Probabilities:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.01854 0.03257 0.03257 0.03040 0.03257 0.03257 
Population size (PSUs): 757 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "fpc"      "pw"      

api> summary(rclus1p)
Call: rclus1p<-postStratify(rclus1, ~stype, pop.types)
Unstratified cluster jacknife (JK1) with 15 replicates and MSE variances.
Variables: 
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "fpc"      "pw"      

api> svymean(~api00, dclus1p)
        mean     SE
api00 642.31 23.921

api> svytotal(~enroll, dclus1p, na.rm=TRUE)
         total     SE
enroll 3680893 406293

api> svymean(~api00, rclus1p)
        mean     SE
api00 642.31 26.936

api> svytotal(~enroll, rclus1p, na.rm=TRUE)
         total     SE
enroll 3680893 473434
> 
> options(survey.replicates.mse=FALSE)
> example(api)

api> library(survey)

api> data(api)

api> mean(apipop$api00)
[1] 664.7126

api> sum(apipop$enroll, na.rm=TRUE)
[1] 3811472

api> #stratified sample
api> dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)

api> summary(dstrat)
Stratified Independent Sampling design
dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)
Probabilities:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.02262 0.02262 0.03587 0.04014 0.05339 0.06623 
Stratum Sizes: 
             E  H  M
obs        100 50 50
design.PSU 100 50 50
actual.PSU 100 50 50
Population stratum sizes (PSUs): 
   E    H    M 
4421  755 1018 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "pw"       "fpc"     

api> svymean(~api00, dstrat)
        mean     SE
api00 662.29 9.4089

api> svytotal(~enroll, dstrat, na.rm=TRUE)
         total     SE
enroll 3687178 114642

api> # one-stage cluster sample
api> dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)

api> summary(dclus1)
1 - level Cluster Sampling design
With (15) clusters.
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
Probabilities:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.02954 0.02954 0.02954 0.02954 0.02954 0.02954 
Population size (PSUs): 757 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "fpc"      "pw"      

api> svymean(~api00, dclus1)
        mean     SE
api00 644.17 23.542

api> svytotal(~enroll, dclus1, na.rm=TRUE)
         total     SE
enroll 3404940 932235

api> # two-stage cluster sample
api> dclus2<-svydesign(id=~dnum+snum, fpc=~fpc1+fpc2, data=apiclus2)

api> summary(dclus2)
2 - level Cluster Sampling design
With (40, 126) clusters.
dclus2<-svydesign(id=~dnum+snum, fpc=~fpc1+fpc2, data=apiclus2)
Probabilities:
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
0.003669 0.037743 0.052840 0.042390 0.052840 0.052840 
Population size (PSUs): 757 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "pw"       "fpc1"     "fpc2"    

api> svymean(~api00, dclus2)
        mean     SE
api00 670.81 30.099

api> svytotal(~enroll, dclus2, na.rm=TRUE)
         total     SE
enroll 2639273 799638

api> # two-stage `with replacement'
api> dclus2wr<-svydesign(id=~dnum+snum, weights=~pw, data=apiclus2)

api> summary(dclus2wr)
2 - level Cluster Sampling design (with replacement)
With (40, 126) clusters.
dclus2wr<-svydesign(id=~dnum+snum, weights=~pw, data=apiclus2)
Probabilities:
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
0.003669 0.037743 0.052840 0.042390 0.052840 0.052840 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "pw"       "fpc1"     "fpc2"    

api> svymean(~api00, dclus2wr)
        mean     SE
api00 670.81 30.712

api> svytotal(~enroll, dclus2wr, na.rm=TRUE)
         total     SE
enroll 2639273 820261

api> # convert to replicate weights
api> rclus1<-as.svrepdesign(dclus1)

api> summary(rclus1)
Call: as.svrepdesign.default(dclus1)
Unstratified cluster jacknife (JK1) with 15 replicates.
Variables: 
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "fpc"      "pw"      

api> svymean(~api00, rclus1)
        mean     SE
api00 644.17 26.329

api> svytotal(~enroll, rclus1, na.rm=TRUE)
         total     SE
enroll 3404940 932235

api> # post-stratify on school type
api> pop.types<-xtabs(~stype, data=apipop)

api> rclus1p<-postStratify(rclus1, ~stype, pop.types)

api> dclus1p<-postStratify(dclus1, ~stype, pop.types)

api> summary(dclus1p)
1 - level Cluster Sampling design
With (15) clusters.
dclus1p<-postStratify(dclus1, ~stype, pop.types)
Probabilities:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.01854 0.03257 0.03257 0.03040 0.03257 0.03257 
Population size (PSUs): 757 
Data variables:
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "fpc"      "pw"      

api> summary(rclus1p)
Call: rclus1p<-postStratify(rclus1, ~stype, pop.types)
Unstratified cluster jacknife (JK1) with 15 replicates.
Variables: 
 [1] "cds"      "stype"    "name"     "sname"    "snum"     "dname"   
 [7] "dnum"     "cname"    "cnum"     "flag"     "pcttest"  "api00"   
[13] "api99"    "target"   "growth"   "sch.wide" "comp.imp" "both"    
[19] "awards"   "meals"    "ell"      "yr.rnd"   "mobility" "acs.k3"  
[25] "acs.46"   "acs.core" "pct.resp" "not.hsg"  "hsg"      "some.col"
[31] "col.grad" "grad.sch" "avg.ed"   "full"     "emer"     "enroll"  
[37] "api.stu"  "fpc"      "pw"      

api> svymean(~api00, dclus1p)
        mean     SE
api00 642.31 23.921

api> svytotal(~enroll, dclus1p, na.rm=TRUE)
         total     SE
enroll 3680893 406293

api> svymean(~api00, rclus1p)
        mean     SE
api00 642.31 26.934

api> svytotal(~enroll, rclus1p, na.rm=TRUE)
         total     SE
enroll 3680893 473431
> 
> proc.time()
   user  system elapsed 
   1.42    0.01    1.43