SGP-package: SGP: An R Package for the Calculation and Visualization of Student Growth Percentiles & Percentile Growth Trajectories.

Description

SGP contains functions to calculate student growth percentiles and percentile growth projections/trajectories following methodology found in Betebenner (2008, 2009). The package contains two primary functions, studentGrowthPercentiles and studentGrowthProjections, and numerous higher level functions that make use of them including: prepareSGP, analyzeSGP, combineSGP, summarizeSGP, and visualizeSGP. These functions are used to calculate and visualize 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 a number of state testing and accountability systems. The functions employ quantile regression (using the quantreg package) to estimate the conditional density for current achievement using each student's achievement history. Percentile growth projections/trajectories are calculated using the coefficient matrices derived from the student growth percentile analyses. These quantities are summarized in a variety of ways to describe student growth. As of the 0.2-0.0 release, the package also includes the graphics functions bubblePlot, studentGrowthPlot, and growthAchievementPlot to produce high quality graphical representations associated with the student growth percentile analyses.

Arguments

Details

ll{ Package: SGP Type: Package Version: 0.7-1.0 Date: 2011-10-11 License: CC BY-SA 3.0 US | CC BY-NC-SA 3.0 + file LICENSE LazyLoad: yes } Calculation of student growth percentiles and percentile growth trajectories/projections 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 and years is provided in the examples of the studentGrowthPercentiles and studentGrowthProjections using the higher level functions prepareSGP, analyzeSGP, combineSGP, summarizeSGP, and visualizeSGP.

References

Betebenner, D. W. (2009). Norm- and criterion-referenced student growth. Educational Measurement: Issues and Practice, 28(4):42-51.

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.

Koenker, R. (2005). Quantile regression. Cambridge: Cambridge University Press.