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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# Install 'OptimalSurrogate' in R:
install.packages('OptimalSurrogate', repos = c('https://laylaparast.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • marker_cont - Simulated data with continuous surrogate marker
  • marker_disc - Simulated data with discrete surrogate marker

On CRAN:

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

2 exports 0.00 score 1 dependencies 2 scripts 149 downloads

Last updated 2 years agofrom:ccba9306a4. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 17 2024
R-4.5-winOKSep 17 2024
R-4.5-linuxOKSep 17 2024
R-4.4-winOKSep 17 2024
R-4.4-macOKSep 17 2024
R-4.3-winOKSep 17 2024
R-4.3-macOKSep 17 2024

Exports:pte_contpte_disc

Dependencies:MASS