SIIdata: SIIdata Data (1190 x 12)

Description Format Details Source Examples


Data from Study of Instructional Improvement Project


The SIIdata data frame has 1190 rows and 12 columns. The dataset includes results for 1190 first grade pupils sampled from 312 classrooms in 107 schools.


a factor with 2 levels M, F,i.e. males and females, resepectively


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 socioeconomical 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 nneighborhood 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


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


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.



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