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:
OptimalSurrogate_1.0.tar.gz
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OptimalSurrogate.pdf |OptimalSurrogate.html✨
OptimalSurrogate/json (API)
| # Install 'OptimalSurrogate' in R: |
| install.packages('OptimalSurrogate', repos = c('https://laylaparast.r-universe.dev', 'https://cloud.r-project.org')) |
- marker_cont - Simulated data with continuous surrogate marker
- marker_disc - Simulated data with discrete surrogate marker
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:ccba9306a4. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 16 2024 |
| R-4.5-win | OK | Nov 16 2024 |
| R-4.5-linux | OK | Nov 16 2024 |
| R-4.4-win | OK | Nov 16 2024 |
| R-4.4-mac | OK | Nov 16 2024 |
| R-4.3-win | OK | Nov 16 2024 |
| R-4.3-mac | OK | Nov 16 2024 |
Dependencies:MASS
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Simulated data with continuous surrogate marker | marker_cont |
| Simulated data with discrete surrogate marker | marker_disc |
| PTE estimation with a continuous surrogate marker | pte_cont |
| PTE estimation with a discrete surrogate marker | pte_disc |
