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).

Getting started

Package details

AuthorWai-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]
MaintainerWai-ki Yip <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the stepp package in your browser

Any scripts or data that you put into this service are public.

stepp documentation built on Jan. 13, 2021, 5:25 p.m.