`api.Rd`

The Academic Performance Index is computed for all California schools based on standardised testing of students. The data sets contain information for all schools with at least 100 students and for various probability samples of the data.

`data(api)`

The full population data in `apipop`

are a data frame with 6194 observations on the following 37 variables.

- cds
Unique identifier

- stype
Elementary/Middle/High School

- name
School name (15 characters)

- sname
School name (40 characters)

- snum
School number

- dname
District name

- dnum
District number

- cname
County name

- cnum
County number

- flag
reason for missing data

- pcttest
percentage of students tested

- api00
API in 2000

- api99
API in 1999

- target
target for change in API

- growth
Change in API

- sch.wide
Met school-wide growth target?

- comp.imp
Met Comparable Improvement target

- both
Met both targets

- awards
Eligible for awards program

- meals
Percentage of students eligible for subsidized meals

- ell
`English Language Learners' (percent)

- yr.rnd
Year-round school

- mobility
percentage of students for whom this is the first year at the school

- acs.k3
average class size years K-3

- acs.46
average class size years 4-6

- acs.core
Number of core academic courses

- pct.resp
percent where parental education level is known

- not.hsg
percent parents not high-school graduates

- hsg
percent parents who are high-school graduates

- some.col
percent parents with some college

- col.grad
percent parents with college degree

- grad.sch
percent parents with postgraduate education

- avg.ed
average parental education level

- full
percent fully qualified teachers

- emer
percent teachers with emergency qualifications

- enroll
number of students enrolled

- api.stu
number of students tested.

The other data sets contain additional variables `pw`

for
sampling weights and `fpc`

to compute finite population
corrections to variance.

`apipop`

is the entire population, `apisrs`

is a simple random sample,
`apiclus1`

is a cluster sample of school districts, `apistrat`

is
a sample stratified by `stype`

, and `apiclus2`

is a two-stage
cluster sample of schools within districts. The sampling weights in
`apiclus1`

are incorrect (the weight should be 757/15) but are as
obtained from UCLA.

Data were obtained from the survey sampling help pages of UCLA Academic Technology Services; these pages are no longer on line.

The API program has been discontinued at the end of 2018. Information is archived at https://www.cde.ca.gov/re/pr/api.asp

```
library(survey)
data(api)
mean(apipop$api00)
#> [1] 664.7126
sum(apipop$enroll, na.rm=TRUE)
#> [1] 3811472
#stratified sample
dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)
summary(dstrat)
#> Stratified Independent Sampling design
#> 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"
svymean(~api00, dstrat)
#> mean SE
#> api00 662.29 9.4089
svytotal(~enroll, dstrat, na.rm=TRUE)
#> total SE
#> enroll 3687178 114642
# one-stage cluster sample
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
summary(dclus1)
#> 1 - level Cluster Sampling design
#> With (15) clusters.
#> 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"
svymean(~api00, dclus1)
#> mean SE
#> api00 644.17 23.542
svytotal(~enroll, dclus1, na.rm=TRUE)
#> total SE
#> enroll 3404940 932235
# two-stage cluster sample
dclus2<-svydesign(id=~dnum+snum, fpc=~fpc1+fpc2, data=apiclus2)
summary(dclus2)
#> 2 - level Cluster Sampling design
#> With (40, 126) clusters.
#> 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"
svymean(~api00, dclus2)
#> mean SE
#> api00 670.81 30.099
svytotal(~enroll, dclus2, na.rm=TRUE)
#> total SE
#> enroll 2639273 799638
# two-stage `with replacement'
dclus2wr<-svydesign(id=~dnum+snum, weights=~pw, data=apiclus2)
summary(dclus2wr)
#> 2 - level Cluster Sampling design (with replacement)
#> With (40, 126) clusters.
#> 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"
svymean(~api00, dclus2wr)
#> mean SE
#> api00 670.81 30.712
svytotal(~enroll, dclus2wr, na.rm=TRUE)
#> total SE
#> enroll 2639273 820261
# convert to replicate weights
rclus1<-as.svrepdesign(dclus1)
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"
svymean(~api00, rclus1)
#> mean SE
#> api00 644.17 26.329
svytotal(~enroll, rclus1, na.rm=TRUE)
#> total SE
#> enroll 3404940 932235
# post-stratify on school type
pop.types<-xtabs(~stype, data=apipop)
rclus1p<-postStratify(rclus1, ~stype, pop.types)
dclus1p<-postStratify(dclus1, ~stype, pop.types)
summary(dclus1p)
#> 1 - level Cluster Sampling design
#> With (15) clusters.
#> 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"
summary(rclus1p)
#> Call: 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"
svymean(~api00, dclus1p)
#> mean SE
#> api00 642.31 23.92
svytotal(~enroll, dclus1p, na.rm=TRUE)
#> total SE
#> enroll 3680893 406293
svymean(~api00, rclus1p)
#> mean SE
#> api00 642.31 26.934
svytotal(~enroll, rclus1p, na.rm=TRUE)
#> total SE
#> enroll 3680893 473431
```