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.
|Imports:||rgl, lattice, latticeExtra, survival, nlme, lme4, OrdinalLogisticBiplot, logistf, rms, mixtools|
|Author:||Wim Van der Elst, Paul Meyvisch, 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)]|
|CRAN checks:||Surrogate results|
|Windows binaries:||r-devel: Surrogate_0.1-801.zip, r-release: Surrogate_0.1-801.zip, r-oldrel: Surrogate_0.1-801.zip|
|OS X El Capitan binaries:||r-release: Surrogate_0.1-801.tgz|
|OS X Mavericks binaries:||r-oldrel: Surrogate_0.1-801.tgz|
|Old sources:||Surrogate archive|
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