STAR {AER} | R Documentation

## Project STAR: Student-Teacher Achievement Ratio

### Description

The Project STAR public access data set, assessing the effect of reducing class size on test scores in the early grades.

### Usage

    data("STAR")

### Format

A data frame containing 11,598 observations on 47 variables.

gender

  factor indicating student's gender.

ethnicity

  factor indicating student's ethnicity with levels `"cauc"` (Caucasian), `"afam"` (African-American), `"asian"` (Asian), `"hispanic"` (Hispanic), `"amindian"` (American-Indian) or `"other"`.

birth

  student's birth quarter (of class `yearqtr`).

stark

  factor indicating the STAR class type in kindergarten: regular, small, or regular-with-aide. `NA` indicates that no STAR class was attended.

star1

  factor indicating the STAR class type in 1st grade: regular, small, or regular-with-aide. `NA` indicates that no STAR class was attended.

star2

  factor indicating the STAR class type in 2nd grade: regular, small, or regular-with-aide. `NA` indicates that no STAR class was attended.

star3

  factor indicating the STAR class type in 3rd grade: regular, small, or regular-with-aide. `NA` indicates that no STAR class was attended.

readk

  total reading scaled score in kindergarten.

read1

  total reading scaled score in 1st grade.

read2

  total reading scaled score in 2nd grade.

read3

  total reading scaled score in 3rd grade.

mathk

  total math scaled score in kindergarten.

math1

  total math scaled score in 1st grade.

math2

  total math scaled score in 2nd grade.

math3

  total math scaled score in 3rd grade.

lunchk

  factor indicating whether the student qualified for free lunch in kindergarten.

lunch1

  factor indicating whether the student qualified for free lunch in 1st grade.

lunch2

  factor indicating whether the student qualified for free lunch in 2nd grade.

lunch3

  factor indicating whether the student qualified for free lunch in 3rd grade.

schoolk

  factor indicating school type in kindergarten: `"inner-city"`, `"suburban"`, `"rural"` or `"urban"`.

school1

  factor indicating school type in 1st grade: `"inner-city"`, `"suburban"`, `"rural"` or `"urban"`.

school2

  factor indicating school type in 2nd grade: `"inner-city"`, `"suburban"`, `"rural"` or `"urban"`.

school3

  factor indicating school type in 3rd grade: `"inner-city"`, `"suburban"`, `"rural"` or `"urban"`.

degreek

  factor indicating highest degree of kindergarten teacher: `"bachelor"`, `"master"`, `"specialist"`, or `"master+"`.

degree1

  factor indicating highest degree of 1st grade teacher: `"bachelor"`, `"master"`, `"specialist"`, or `"phd"`.

degree2

  factor indicating highest degree of 2nd grade teacher: `"bachelor"`, `"master"`, `"specialist"`, or `"phd"`.

degree3

  factor indicating highest degree of 3rd grade teacher: `"bachelor"`, `"master"`, `"specialist"`, or `"phd"`.

ladderk

  factor indicating teacher's career ladder level in kindergarten: `"level1"`, `"level2"`, `"level3"`, `"apprentice"`, `"probation"` or `"pending"`.

ladder1

  factor indicating teacher's career ladder level in 1st grade: `"level1"`, `"level2"`, `"level3"`, `"apprentice"`, `"probation"` or `"noladder"`.

ladder2

  factor indicating teacher's career ladder level in 2nd grade: `"level1"`, `"level2"`, `"level3"`, `"apprentice"`, `"probation"` or `"noladder"`.

ladder3

  factor indicating teacher's career ladder level in 3rd grade: `"level1"`, `"level2"`, `"level3"`, `"apprentice"`, `"probation"` or `"noladder"`.

experiencek

  years of teacher's total teaching experience in kindergarten.

experience1

  years of teacher's total teaching experience in 1st grade.

experience2

  years of teacher's total teaching experience in 2nd grade.

experience3

  years of teacher's total teaching experience in 3rd grade.

tethnicityk

  factor indicating teacher's ethnicity in kindergarten with levels `"cauc"` (Caucasian) or `"afam"` (African-American).

tethnicity1

  factor indicating teacher's ethnicity in 1st grade with levels `"cauc"` (Caucasian) or `"afam"` (African-American).

tethnicity2

  factor indicating teacher's ethnicity in 2nd grade with levels `"cauc"` (Caucasian) or `"afam"` (African-American).

tethnicity3

  factor indicating teacher's ethnicity in 3rd grade with levels `"cauc"` (Caucasian), `"afam"` (African-American), or `"asian"` (Asian).

systemk

  factor indicating school system ID in kindergarten.

system1

  factor indicating school system ID in 1st grade.

system2

  factor indicating school system ID in 2nd grade.

system3

  factor indicating school system ID in 3rd grade.

schoolidk

  factor indicating school ID in kindergarten.

schoolid1

  factor indicating school ID in 1st grade.

schoolid2

  factor indicating school ID in 2nd grade.

schoolid3

  factor indicating school ID in 3rd grade.

### Details

Project STAR (Student/Teacher Achievement Ratio) was a four-year longitudinal class-size study funded by the Tennessee General Assembly and conducted in the late 1980s by the State Department of Education. Over 7,000 students in 79 schools were randomly assigned into one of three interventions: small class (13 to 17 students per teacher), regular class (22 to 25 students per teacher), and regular-with-aide class (22 to 25 students with a full-time teacher's aide). Classroom teachers were also randomly assigned to the classes they would teach. The interventions were initiated as the students entered school in kindergarten and continued through third grade.

The Project STAR public access data set contains data on test scores, treatment groups, and student and teacher characteristics for the four years of the experiment, from academic year 1985–1986 to academic year 1988–1989. The test score data analyzed in this chapter are the sum of the scores on the math and reading portion of the Stanford Achievement Test.

Stock and Watson (2007) obtained the data set from the Project STAR Web site at http://www.heros-inc.org/star.htm.

The data is provided in wide format. Reshaping it into long format is illustrated below. Note that the levels of the `degree`, `ladder` and `tethnicity` variables differ slightly between kindergarten and higher grades.

### Source

Online complements to Stock and Watson (2007).

### References

Stock, J.H. and Watson, M.W. (2007). Introduction to Econometrics, 2nd ed. Boston: Addison Wesley.

### See Also

`StockWatson2007`

### Examples

    data("STAR")

    ## Stock and Watson, p. 488
    fmk <- lm(I(readk + mathk) ~ stark, data = STAR)
    fm1 <- lm(I(read1 + math1) ~ star1, data = STAR)
    fm2 <- lm(I(read2 + math2) ~ star2, data = STAR)
    fm3 <- lm(I(read3 + math3) ~ star3, data = STAR)

    coeftest(fm3, vcov = sandwich)
    plot(I(read3 + math3) ~ star3, data = STAR)

    ## Stock and Watson, p. 489
    fmke <- lm(I(readk + mathk) ~ stark + experiencek, data = STAR)
    coeftest(fmke, vcov = sandwich)

    ## reshape data from wide into long format
    ## 1. variables and their levels
    nam <- c("star", "read", "math", "lunch", "school", "degree", "ladder",
      "experience", "tethnicity", "system", "schoolid")
    lev <- c("k", "1", "2", "3")
    ## 2. reshaping
    star <- reshape(STAR, idvar = "id", ids = row.names(STAR),
      times = lev, timevar = "grade", direction = "long",
      varying = lapply(nam, function(x) paste(x, lev, sep = "")))
    ## 3. improve variable names and type
    names(star)[5:15] <- nam
    star$id <- factor(star$id)
    star$grade <- factor(star$grade, levels = lev, labels = c("kindergarten", "1st", "2nd", "3rd"))
    rm(nam, lev)

    ## fit a single model nested in grade (equivalent to fmk, fm1, fm2, fmk)
    fm <- lm(I(read + math) ~ 0 + grade/star, data = star)
    coeftest(fm, vcov = sandwich)

    ## visualization
    library("lattice")
    bwplot(I(read + math) ~ star | grade, data = star)

[Package AER version 1.2-5 Index]