studentGrowthPercentiles
and studentGrowthProjections
, and numerous higher level functions
that make use of them including: prepareSGP
, analyzeSGP
, combineSGP
, summarizeSGP
, visualizeSGP
and
outputSGP
. 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- and criterion-referenced growth values are currently used in a number of states for many purposes including diagnostic and accountability.
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.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
.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.