Package: OptimalSurrogate 1.0

OptimalSurrogate: Model Free Approach to Quantifying Surrogacy

Identifies an optimal transformation of a surrogate marker such that the proportion of treatment effect explained can be inferred based on the transformation of the surrogate and nonparametrically estimates two model-free quantities of this proportion. Details are described in Wang et al (2020) <doi:10.1093/biomet/asz065>.

Authors:Xuan Wang [aut], Layla Parast [aut, cre], Ming Yang [aut], Lu Tian [aut], Tianxi Cai [aut]

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manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
OptimalSurrogate/json (API)

# Install 'OptimalSurrogate' in R:
install.packages('OptimalSurrogate', repos = c('https://laylaparast.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • marker_cont - Simulated data with continuous surrogate marker
  • marker_disc - Simulated data with discrete surrogate marker

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 2 scripts 208 downloads 2 exports 1 dependencies

Last updated from:ccba9306a4. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK106
source / vignettesOK156
linux-release-x86_64OK103
macos-release-arm64OK117
macos-oldrel-arm64OK60
windows-develOK65
windows-releaseOK63
windows-oldrelOK63
wasm-releaseOK94

Exports:pte_contpte_disc

Dependencies:MASS