In a clinical trial, it frequently occurs that the most credible
outcome to evaluate the effectiveness of a new therapy (the true endpoint) is
difficult to measure. In such a situation, it can be an effective strategy to
replace the true endpoint by a (bio)marker that is easier to measure and that
allows for a prediction of the treatment effect on the true endpoint (a
surrogate endpoint). The package 'Surrogate' allows for an evaluation of the
appropriateness of a candidate surrogate endpoint based on the meta-analytic,
information-theoretic, and causal-inference frameworks. Part of this software
has been developed using funding provided from the European Union's Seventh
Framework Programme for research, technological development and demonstration
(Grant Agreement no 602552), the Special Research Fund (BOF) of Hasselt
University (BOF-number: BOF2OCPO3), GlaxoSmithKline Biologicals, Baekeland
Mandaat (HBC.2022.0145), and Johnson & Johnson Innovative Medicine.
Version: |
3.3.0 |
Depends: |
R (≥ 3.5.0) |
Imports: |
MASS, lattice, latticeExtra, survival, nlme, lme4, msm, logistf, rms, ks, extraDistr, pbapply, flexsurv, rvinecopulib, maxLik, purrr, MBESS, tidyr, dplyr, numDeriv, optimx, tibble |
Suggests: |
copula, FNN, mgcv, testthat (≥ 3.0.0), vdiffr, parallel, fitdistrplus, kdecopula, cubature, mvtnorm, withr, stringr, ggplot2 |
Published: |
2024-06-12 |
DOI: |
10.32614/CRAN.package.Surrogate |
Author: |
Wim Van Der Elst [cre, aut],
Florian Stijven [aut],
Fenny Ong [aut],
Dries De Witte [aut],
Paul Meyvisch [aut],
Alvaro Poveda [aut],
Ariel Alonso [aut],
Hannah Ensor [aut],
Christoper Weir [aut],
Geert Molenberghs [aut] |
Maintainer: |
Wim Van Der Elst <wim.vanderelst at gmail.com> |
BugReports: |
https://github.com/florianstijven/Surrogate-development/issues |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: |
https://github.com/florianstijven/Surrogate-development |
NeedsCompilation: |
no |
Materials: |
README NEWS |
CRAN checks: |
Surrogate results |