Functions to calculate student growth percentiles and percentile growth projections/trajectories for students using large scale, longitudinal assessment data. Functions use quantile regression to estimate the conditional density associated with each student's achievement history. Percentile growth projections/trajectories are calculated using th…
R
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Minor mods to speed up executation

README.md

The SGP Package is open source software built for the R software environment. The classes, functions and data within the SGP package are used to calculate student growth percentiles and percentile growth projections/trajectories using large scale, longitudinal assessment data. Quantile regression is used to estimate the conditional density associated with each student's achievement history. Percentile growth projections/trajectories are calculated using the derived coefficient matrices and show the percentile growth needed to reach future achievement targets.

Build Status CRAN_Status_Badge Development Version Rstudio mirror downloads License Join the chat at https://gitter.im/CenterForAssessment/SGP

SGP Resources

Contributors

The SGP Package is crafted with ❤️ by:

We love feedback and are happy to answer questions.

Install the latest stable release from CRAN

install.packages("SGP")
require(SGP)

Install latest development release from Github :octocat:

install.packages("devtools")
require(devtools)
install_github("CenterForAssessment/SGP")
require(SGP)

To install from Github you might need: Windows: Rtools, OS X: xcode (from the app store), Linux: apt-get install r-base-dev (or similar).

To use the SGP Package

  • The SGP Package Wiki contains instructions on how to prepare data and run SGP analyses.
  • The SGP Package Documentation contains man pages for all functions and data sets in the the SGP Package.
  • Numerous SGP Gists provide other examples of analyses that can be performed.

References

Betebenner, D. W., VanIwaarden, A., Domingue, B., and Shang, Y. (2016). SGP: Student Growth Percentiles & Percentile Growth Trajectories.

R Development Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 3-900051-07-0.