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 under Grant Agreement no 602552.
| Version: | 1.7 |
| Imports: | MASS, rgl, lattice, latticeExtra, survival, nlme, lme4, msm, OrdinalLogisticBiplot, logistf, rms, mixtools, parallel, ks, rootSolve, extraDistr |
| Published: | 2020-03-23 |
| Author: | Wim Van der Elst, Paul Meyvisch, Alvaro Florez Poveda, Ariel Alonso, Hannah M. Ensor, Christopher J. Weir & Geert Molenberghs |
| Maintainer: | Wim Van der Elst <Wim.vanderelst at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | Surrogate results |
| Reference manual: | Surrogate.pdf |
| Package source: | Surrogate_1.7.tar.gz |
| Windows binaries: | r-devel: Surrogate_1.7.zip, r-release: Surrogate_1.7.zip, r-oldrel: Surrogate_1.7.zip |
| macOS binaries: | r-release: Surrogate_1.7.tgz, r-oldrel: Surrogate_1.7.tgz |
| Old sources: | Surrogate archive |
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