SGP-package {SGP} | R Documentation |
SGP contains two functions, studentGrowthPercentiles
and studentGrowthProjections
, used to calculate
student growth percentiles and percentile growth projections/trajectories for students using large scale, longitudinal assessment data. These norm referenced growth values
are currently used in state testing and accountability systems. The functions employ quantile regression (using the quantreg
package) to estimate the conditional density associated with each student's achievement history. Percentile growth projections/trajectories
are calculated using the coefficient matrices derived from the student growth percentile analyses.
Package: | SGP |
Type: | Package |
Version: | 0.0-3 |
Date: | 2009-2-15 |
License: | Creative Commons Attribution + ShareAlike (by-sa) |
LazyLoad: | yes |
Calculation of student growth percentiles is typically performed by grade and subject. Data for growth percentile calculation must be specifically formatted.
See sgpData
for an example data set. Batch R syntax for performing analyses across all grades is provided in the examples of the studentGrowthPercentiles
and
studentGrowthProjections
functions. Calculation of percentile growth projections/trajectories follows calculation of student growth percentiles and requires coefficient matrices
derived during student growth percentile estimation.
Damian W. Betebenner DBetebenner@nciea.org
Koenker, R. (2005). Quantile regression. Cambridge: Cambridge University Press.
Betebenner, D. W. (2008). Toward a normative understanding of student growth. In K. E. Ryan & L. A. Shepard (Eds.), The Future of Test Based Accountability (pp. 155-170). New York: Routledge.