api {survey} | R Documentation

## Student performance in California schools

### Description

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.

### Usage

    data(api)

### Format

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.

### Details

`apipop` is the entire population, `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.

### Source

Data were obtained from the survey sampling help pages of UCLA Academic Technology Services, at http://www.ats.ucla.edu/stat/stata/Library/svy_survey.htm.

### References

The API program and original data files are at http://api.cde.ca.gov/

### Examples

    library(survey)
    data(api)
    mean(apipop$api00)
    sum(apipop$enroll, na.rm=TRUE)

    #stratified sample
    dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)
    summary(dstrat)
    svymean(~api00, dstrat)
    svytotal(~enroll, dstrat, na.rm=TRUE)

    # one-stage cluster sample
    dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)
    summary(dclus1)
    svymean(~api00, dclus1)
    svytotal(~enroll, dclus1, na.rm=TRUE)

    # two-stage cluster sample
    dclus2<-svydesign(id=~dnum+snum, fpc=~fpc1+fpc2, data=apiclus2)
    summary(dclus2)
    svymean(~api00, dclus2)
    svytotal(~enroll, dclus2, na.rm=TRUE)

    # two-stage `with replacement'
    dclus2wr<-svydesign(id=~dnum+snum, weights=~pw, data=apiclus2)
    summary(dclus2wr)
    svymean(~api00, dclus2wr)
    svytotal(~enroll, dclus2wr, na.rm=TRUE)

    # convert to replicate weights
    rclus1<-as.svrepdesign(dclus1)
    summary(rclus1)
    svymean(~api00, rclus1)
    svytotal(~enroll, rclus1, na.rm=TRUE)

    # 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)
    summary(rclus1p)

    svymean(~api00, dclus1p)
    svytotal(~enroll, dclus1p, na.rm=TRUE)

    svymean(~api00, rclus1p)
    svytotal(~enroll, rclus1p, na.rm=TRUE)

[Package survey version 3.19 Index]