stepp: Subpopulation Treatment Effect Pattern Plot (STEPP)

A method to explore the treatment-covariate interactions in survival or generalized linear model (GLM) for continuous, binomial and count data arising from two or more treatment arms of a clinical trial. A permutation distribution approach to inference is implemented, based on permuting the covariate values within each treatment group. Bonetti M, Gelber RD (2004) <doi:10.1093/biostatistics/5.3.465>. Marco Bonetti, David Zahrieh, Bernard F. Cole, and Richard D. Gelber (2009) <doi:10.1002/sim.3524>. Ann A. Lazar, Bernard F. Cole, Marco Bonetti, and Richard D. Gelber (2010) <doi:10.1200/JCO.2009.27.9182>. Lazar AA,Bonetti M,Cole BF,Yip WK,Gelber RD (2016) <doi:10.1177/1740774515609106>. Wai-Ki Yip,Marco Bonetti,Bernard F Cole,William Barcella,Xin Victoria Wang,Ann Lazar,and Richard D Gelber (2016) <doi:10.1177/1740774516643297>. Wang XV, Cole B, Bonetti M, Gelber RD (2016) <doi:10.1002/sim.6958>. Wai-Ki Yip (2017, ISBN:978-3-319-48846-2).

Version: 3.2.2
Depends: methods, car, survival, splines
Imports: rstudioapi, scales
Published: 2021-01-11
Author: Wai-ki Yip [aut, cre], Ann Lazar [ctb], David Zahrieh [ctb], Chip Cole [ctb], Ann Lazar [ctb], Marco Bonetti [ctb], Victoria Wang [ctb], William Barcella [ctb], Sergio Venturini [ctb, cre] Richard Gelber [ctb]
Maintainer: Wai-ki Yip <yuser86 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: stepp results


Reference manual: stepp.pdf
Package source: stepp_3.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: stepp_3.2.2.tgz, r-oldrel: stepp_3.2.2.tgz
Old sources: stepp archive


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