Package: Rsurrogate 3.1

Rsurrogate: Robust Estimation of the Proportion of Treatment Effect Explained by Surrogate Marker Information

Provides functions to estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on the surrogate marker.

Authors:Layla Parast

Rsurrogate_3.1.tar.gz
Rsurrogate_3.1.zip(r-4.5)Rsurrogate_3.1.zip(r-4.4)Rsurrogate_3.1.zip(r-4.3)
Rsurrogate_3.1.tgz(r-4.5-any)Rsurrogate_3.1.tgz(r-4.4-any)Rsurrogate_3.1.tgz(r-4.3-any)
Rsurrogate_3.1.tar.gz(r-4.5-noble)Rsurrogate_3.1.tar.gz(r-4.4-noble)
Rsurrogate_3.1.tgz(r-4.4-emscripten)Rsurrogate_3.1.tgz(r-4.3-emscripten)
Rsurrogate.pdf |Rsurrogate.html✨
Rsurrogate/json (API)

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

Bug tracker:https://github.com/laylaparast/rsurrogate/issues

Datasets:

On CRAN:

Conda:

3.16 score 4 packages 12 scripts 270 downloads 25 exports 3 dependencies

Last updated 3 years agofrom:80ac29096e. Checks:3 OK, 6 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 05 2025
R-4.5-winNOTEMar 05 2025
R-4.5-macNOTEMar 05 2025
R-4.5-linuxNOTEMar 05 2025
R-4.4-winNOTEMar 05 2025
R-4.4-macNOTEMar 05 2025
R-4.4-linuxNOTEMar 05 2025
R-4.3-winOKMar 05 2025
R-4.3-macOKMar 05 2025

Exports:Aug.R.s.surv.estimateaugment.est.vectorcalculate.var.npcensor.weightcumsum2delta.estimatedelta.multiple.survdelta.s.estimatedelta.s.surv.estimatedelta.surv.estimatedelta.t.surv.estimatefieller.calculate.mefieller.cihelper.siKern.FUNme.variance.estimateperturb.nu.vectorpred.smoothpred.smooth.survR.multiple.survR.s.estimateR.s.estimate.meR.s.surv.estimateR.t.surv.estimateVTM

Dependencies:latticeMatrixsurvival

Readme and manuals

Help Manual

Help pageTopics
Calculates the augmented estimator of the proportion of treatment effect explained by the surrogate marker information measured at a specified time and primary outcome information up to that specified timeAug.R.s.surv.estimate
Hypothetical datad_example
Hypothetical survival data with multiple surrogate markersd_example_multiple
Hypothetical survival datad_example_surv
Calculates treatment effectdelta.estimate
Calculates robust residual treatment effect accounting for multiple surrogate markers at a specified time and primary outcome information up to that specified timedelta.multiple.surv
Calculates model-based or robust residual treatment effectdelta.s.estimate
Calculates robust residual treatment effect accounting for surrogate marker information measured at a specified time and primary outcome information up to that specified timedelta.s.surv.estimate
Calculates treatment effect in a survival settingdelta.surv.estimate
Calculates robust residual treatment effect accounting only for primary outcome information up to a specified timedelta.t.surv.estimate
Constructs Fieller's confidence interval.fieller.ci
Estimates measurement error variance given replicate data.me.variance.estimate
Calculates the proportion of treatment effect explained by multiple surrogate markers measured at a specified time and primary outcome information up to that specified timeR.multiple.surv
Calculates the proportion of treatment effect explainedR.s.estimate
Calculates the proportion of treatment effect explained correcting for measurement error in the surrogate markerR.s.estimate.me
Calculates the proportion of treatment effect explained by the surrogate marker information measured at a specified time and primary outcome information up to that specified timeR.s.surv.estimate
Calculates the proportion of treatment effect explained by the primary outcome information up to a specified timeR.t.surv.estimate