api: Student performance in California schools

In bschneidr/fastsurvey: Analysis of Complex Survey Samples

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, 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.

Source

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

References

The API program has been discontinued at the end of 2018, and the archive page at the California Department of Education is now gone. The Wikipedia article has links to past material at the Internet Archive. https://en.wikipedia.org/wiki/Academic_Performance_Index_(California_public_schools)

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)

bschneidr/fastsurvey documentation built on March 13, 2024, 11:12 a.m.