DIFboost: Detection of Differential Item Functioning (DIF) in Rasch Models by Boosting Techniques

Performs detection of Differential Item Functioning using the method DIFboost as proposed in Schauberger and Tutz (2015): Detection of Differential item functioning in Rasch models by boosting techniques, British Journal of Mathematical and Statistical Psychology.

Version: 0.1
Imports: mboost, penalized, stabs
Published: 2015-08-19
Author: Gunther Schauberger
Maintainer: Gunther Schauberger <gunther at stat.uni-muenchen.de>
License: GPL-2
NeedsCompilation: no
CRAN checks: DIFboost results


Reference manual: DIFboost.pdf
Package source: DIFboost_0.1.tar.gz
Windows binaries: r-devel: DIFboost_0.1.zip, r-release: DIFboost_0.1.zip, r-oldrel: DIFboost_0.1.zip
OS X Snow Leopard binaries: r-release: DIFboost_0.1.tgz, r-oldrel: not available
OS X Mavericks binaries: r-release: DIFboost_0.1.tgz