Data from Study of Instructional Improvement Project
SIIdataA data frame with 1190 rows and 12 columns:
A factor with 2 levels: M, F, i.e., males and females, respectively
A factor with 2 levels: Mnrt=No, Mnrt=Yes. An indicator variable for the minority status
An integer vector with values from 290 to 629. This is pupil's math score in the spring of the kindergarten year
An integer vector with values from -110 to 253. Number represents pupil's gain in the math achievement score from the spring of kindergarten to the spring of first grade
A numeric vector with values from -1.61 to 3.21. Value represents socioeconomic status
A numeric vector with values from 0 to 40. It is number of years of teacher's experience in teaching in the first grade
A numeric vector with values from -2.5 to 2.61. Number represents teacher's knowledge of the first-grade math contents (higher values indicate a higher knowledge of the contents)
A numeric vector containing proportion of households in the neighborhood of the school below the poverty level with values ranging from 0.012 to 0.564
A numeric vector with values from 1 to 6. Contains the number of preparatory courses on the first-grade math contents and methods followed by the teacher
A factor with 312 levels: 1, 2, 3, 4, 5, ..., 312. Classroom's id
A factor with 107 levels: 1, 2, 3, 4, 5, ..., 107. School's id
A factor with 1190 levels: 1, 2, 3, 4, 5, ..., 1190. Pupil's id
Hill, H., Rowan, B., and Ball, D. (2005). Effect of teachers' mathematical knowledge for teaching on student achievement. American Educational Research Journal, 42, 371-406. West, B. T., Welch, K. B., and Galecki, A. T. (2007). Linear Mixed Models: A Practical Guide Using Statistical Software. Chapman and Hall/CRC.
The SII Project was carried out to assess the math achievement scores of
first- and third-grade pupils in randomly selected classrooms from a national
US sample of elementary schools (Hill et al, 2005). Data were also analyzed
in West et al, 2007. The outcome of interest is mathgain variable.
Data were created based on classroom data from WWGbook package.
data(SIIdata, package = "nlmeU")
summary(SIIdata)
#> sex minority mathkind mathgain ses
#> M:588 Mnrt=No :384 Min. :290.0 Min. :-110.00 Min. :-1.61000
#> F:602 Mnrt=Yes:806 1st Qu.:439.2 1st Qu.: 35.00 1st Qu.:-0.49000
#> Median :466.0 Median : 56.00 Median :-0.03000
#> Mean :466.7 Mean : 57.57 Mean :-0.01298
#> 3rd Qu.:495.0 3rd Qu.: 77.00 3rd Qu.: 0.39750
#> Max. :629.0 Max. : 253.00 Max. : 3.21000
#>
#> yearstea mathknow housepov mathprep
#> Min. : 0.00 Min. :-2.5000 Min. :0.0120 Min. :1.000
#> 1st Qu.: 4.00 1st Qu.:-0.7200 1st Qu.:0.0850 1st Qu.:2.000
#> Median :10.00 Median :-0.1300 Median :0.1270 Median :2.300
#> Mean :12.21 Mean : 0.0312 Mean :0.1782 Mean :2.612
#> 3rd Qu.:20.00 3rd Qu.: 0.8500 3rd Qu.:0.2550 3rd Qu.:3.000
#> Max. :40.00 Max. : 2.6100 Max. :0.5640 Max. :6.000
#> NA's :109
#> classid schoolid childid
#> 26 : 10 11 : 31 1 : 1
#> 42 : 10 12 : 27 2 : 1
#> 13 : 9 71 : 27 3 : 1
#> 189 : 9 76 : 27 4 : 1
#> 205 : 9 77 : 24 5 : 1
#> 253 : 9 31 : 22 6 : 1
#> (Other):1134 (Other):1032 (Other):1184