simml: Single-Index Models with Multiple-Links

A major challenge in estimating treatment decision rules from a randomized clinical trial dataset with covariates measured at baseline lies in detecting relatively small treatment effect modification-related variability (i.e., the treatment-by-covariates interaction effects on treatment outcomes) against a relatively large non-treatment-related variability (i.e., the main effects of covariates on treatment outcomes). The class of Single-Index Models with Multiple-Links is a novel single-index model specifically designed to estimate a single-index (a linear combination) of the covariates associated with the treatment effect modification-related variability, while allowing a nonlinear association with the treatment outcomes via flexible link functions. The models provide a flexible regression approach to developing treatment decision rules based on patients' data measured at baseline. We refer to Park, Petkova, Tarpey, and Ogden (2020) <doi:10.1016/j.jspi.2019.05.008> and Park, Petkova, Tarpey, and Ogden (2020) <doi:10.1111/biom.13320> (that allows an unspecified X main effect) for detail of the method. The main function of this package is simml().

Version: 0.2.0
Imports: mgcv
Published: 2021-02-09
Author: Hyung Park, Eva Petkova, Thaddeus Tarpey, R. Todd Ogden
Maintainer: Hyung Park <parkh15 at nyu.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: simml results

Downloads:

Reference manual: simml.pdf
Package source: simml_0.2.0.tar.gz
Windows binaries: r-devel: simml_0.2.0.zip, r-release: simml_0.2.0.zip, r-oldrel: simml_0.2.0.zip
macOS binaries: r-release: simml_0.2.0.tgz, r-oldrel: simml_0.2.0.tgz
Old sources: simml archive

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