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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: | 0.3.0 |
| Imports: | mgcv |
| Published: | 2021-05-25 |
| DOI: | 10.32614/CRAN.package.simml |
| Author: | Hyung Park, Eva Petkova, Thaddeus Tarpey, R. Todd Ogden |
| Maintainer: | Hyung Park <parkh15 at nyu.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| In views: | CausalInference |
| CRAN checks: | simml results |
| Reference manual: | simml.pdf |
| Package source: | simml_0.3.0.tar.gz |
| Windows binaries: | r-devel: simml_0.3.0.zip, r-release: simml_0.3.0.zip, r-oldrel: simml_0.3.0.zip |
| macOS binaries: | r-release (arm64): simml_0.3.0.tgz, r-oldrel (arm64): simml_0.3.0.tgz, r-release (x86_64): simml_0.3.0.tgz, r-oldrel (x86_64): simml_0.3.0.tgz |
| Old sources: | simml archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.