Package: SGP
Version: 0.0-6.6
Date: 2010-12-23
Title: Student Growth Percentile and Percentile Growth
Projection/Trajectory Functions
Depends: R (>= 2.7.0), data.table, grid, gtools, quantreg, plyr,
splines
Author: Damian W. Betebenner <dbetebenner@nciea.org>, with
contributions from Adam Van Iwaarden, Jonathan Weeks, Jinnie
Choi, Marie Huchton, Xin Wei, and Hi Shin Shim
Maintainer: Damian W. Betebenner <dbetebenner@nciea.org>
Description: 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 the
coefficient matrices derived from the quantile regression
analyses and specify what percentile growth is required for
students to reach future achievement targets.
LazyLoad: Yes
LazyData: Yes
License: GPL-3 | file LICENSE
Repository: CRAN
Repository/R-Forge/Project: sgp
Repository/R-Forge/Revision: 70
Date/Publication: 2010-12-24 15:28:09
Packaged: 2010-12-23 21:44:02 UTC; rforge

contributions from Adam Van Iwaarden, Jonathan Weeks, John
Stewart, Jinnie Choi, Marie Huchton, Xin Wei, and Hi Shin Shim
Depends: R (>= 2.10), data.table, grid, gtools, plyr, quantreg, sn,

Depends: R (>= 2.10), data.table (>= 1.5.3), foreach, grid, gtools,

Package: SGP
Version: 0.0-6
Date: 2010-09-30
Title: Student Growth Percentile and Percentile Growth
Projection/Trajectory Functions
Depends: R (>= 2.7.0), splines, quantreg, grid, gtools, data.table,
reshape
Author: Damian W. Betebenner <dbetebenner@nciea.org>, with
contributions from Adam Van Iwaarden, Jonathan Weeks, Jinnie
Choi, Marie Huchton, Xin Wei, and Hi Shin Shim
Maintainer: Damian W. Betebenner <dbetebenner@nciea.org>
Description: 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 students achievement history.  Percentile
growth projections/trajectories are calculated using the
coefficient matrices derived from the quantile regression
analyses and specify what percentile growth is required for
students to reach future achievement targets.
LazyLoad: Yes
LazyData: Yes
License: file LICENSE
Repository: CRAN
Repository/R-Forge/Project: sgp
Repository/R-Forge/Revision: 17
Date/Publication: 2010-10-06 06:30:05
Packaged: 2010-10-04 20:39:57 UTC; rforge