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 Petkova, Tarpey, Su, and Ogden (2017) <doi:10.1093/biostatistics/kxw035> and "A constrained single-index model for estimating interactions between a treatment and covariates" (under review, 2019) for detail. The main function of this package is simml().

Version: 0.1.0
Imports: mgcv, plyr
Published: 2019-05-24
Author: Park, H., Petkova, E., Tarpey, T., Ogden, R.T.
Maintainer: Hyung Park <parkh15 at>
License: GPL-3
NeedsCompilation: no
CRAN checks: simml results


Reference manual: simml.pdf
Package source: simml_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: simml_0.1.0.tgz, r-oldrel: simml_0.1.0.tgz


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