subtee: Subgroup Treatment Effect Estimation in Clinical Trials

Naive and adjusted treatment effect estimation for subgroups. Model averaging (Bornkamp et.al, 2016 <doi:10.1002/pst.1796>) and bagging (Rosenkranz, 2016 <doi:10.1002/bimj.201500147>) are proposed to address the problem of selection bias in treatment effect estimates for subgroups. The package can be used for all commonly encountered type of outcomes in clinical trials (continuous, binary, survival, count). Additional functions are provided to build the subgroup variables to be used and to plot the results using forest plots.

Version: 0.3-4
Depends: R (≥ 2.10)
Imports: MASS, ggplot2, survival, matrixStats
Suggests: knitr, parallel
Published: 2019-01-07
Author: Nicolas Ballarini [aut, cre], Bjoern Bornkamp [aut], Marius Thomas [aut, cre], Baldur Magnusson [ctb]
Maintainer: Nicolas Ballarini <nicolas.ballarini at meduniwien.ac.at>
License: GPL-2
NeedsCompilation: no
Materials: NEWS
CRAN checks: subtee results

Downloads:

Reference manual: subtee.pdf
Vignettes: The subtee plot function
The subtee subbuild function
Introduction to subtee and Usage Instructions
Package source: subtee_0.3-4.tar.gz
Windows binaries: r-devel: subtee_0.3-4.zip, r-release: subtee_0.3-4.zip, r-oldrel: subtee_0.3-4.zip
OS X binaries: r-release: subtee_0.3-4.tgz, r-oldrel: subtee_0.3-4.tgz
Old sources: subtee archive

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