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Surrogate

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Evaluation of Surrogate Endpoints in Clinical Trials

View on CRAN: Click here

Download and install Surrogate package within the R console
Install from CRAN:

 install.packages("Surrogate")

Install from Github:

 library("remotes")

                        install_github("cran/Surrogate")

Install by package version:

 library("remotes")

                        install_version("Surrogate", "3.3.3")

Attach the package and use:

 library("Surrogate")

Maintained by
Wim Van Der Elst
[Scholar Profile | Author Map]

All associated links for this package

10.32614/CRAN.package.Surrogate . https://github.com/florianstijven/Surrogate-development/issues . https://github.com/florianstijven/Surrogate-development . Surrogate results . Surrogate.pdf . Surrogate_3.4.0.tar.gz . Surrogate_3.4.0.zip . Surrogate_3.4.0.zip . Surrogate_3.3.3.zip . Surrogate_3.4.0.tgz . Surrogate_3.4.0.tgz . Surrogate_3.4.0.tgz . Surrogate_3.4.0.tgz . Surrogate_3.4.0.tgz . Surrogate_3.4.0.tgz . Surrogate archive . https://CRAN.R-project.org/package=Surrogate .

First Published: 2014-03-19

Latest Update: 2023-09-01

Description:

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.

How to cite:

Wim Van Der Elst (2014). Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials. R package version 3.3.3, https://cran.r-project.org/web/packages/Surrogate. Accessed 11 Apr. 2025.

Previous versions and publish date:

0.1-0 (2014-03-19 12:19), 0.1-1 (2014-05-12 00:56), 0.1-2 (2014-07-30 15:58), 0.1-3 (2014-10-25 01:16), 0.1-4 (2014-12-12 21:30), 0.1-5 (2015-03-26 17:17), 0.1-6 (2015-05-15 00:12), 0.1-61 (2015-06-11 18:31), 0.1-62 (2015-08-25 01:13), 0.1-63 (2015-10-10 01:02), 0.1-64 (2015-11-21 15:56), 0.1-66 (2016-01-23 01:11), 0.1-67 (2016-02-05 19:26), 0.1-68 (2016-02-21 19:51), 0.1-69 (2016-03-18 18:34), 0.1-71 (2016-04-01 16:40), 0.1-72 (2016-04-23 14:41), 0.1-73 (2016-05-16 14:33), 0.1-74 (2016-07-27 11:52), 0.1-75 (2016-09-03 16:39), 0.1-76 (2016-09-24 13:58), 0.1-77 (2016-10-01 15:03), 0.1-79 (2016-10-28 00:05), 0.1-801 (2017-03-05 17:31), 0.2 (2017-06-05 10:38), 0.4 (2017-08-18 18:10), 0.5 (2017-10-08 23:18), 0.6 (2018-01-20 10:27), 0.7 (2018-04-20 22:23), 0.8 (2018-06-02 06:58), 0.9 (2018-06-09 17:46), 1.0 (2018-10-10 12:00), 1.1 (2018-10-18 21:50), 1.2 (2019-02-06 06:43), 1.3 (2019-09-22 15:20), 1.4 (2019-10-26 08:10), 1.5 (2019-12-06 21:50), 1.6 (2020-01-29 16:10), 1.7 (2020-03-23 02:10), 1.8 (2020-12-13 18:00), 1.9 (2021-07-06 18:00), 2.0 (2021-09-28 19:50), 2.1 (2022-06-08 14:50), 2.2 (2022-06-18 10:00), 2.3 (2022-07-08 18:30), 2.4 (2022-08-13 17:20), 2.5 (2022-11-30 10:50), 2.6 (2023-01-22 17:40), 2.7 (2023-02-13 10:20), 2.8 (2023-03-07 10:30), 3.0 (2023-06-22 08:20), 3.1 (2023-09-01 17:20), 3.2.0 (2023-09-06 16:50), 3.2.1 (2023-09-25 11:10), 3.2.2 (2024-02-20 11:10), 3.2.4 (2024-02-29 22:32), 3.2.5 (2024-03-19 15:00), 3.2.6 (2024-05-27 14:30), 3.3.0 (2024-06-12 09:10), 3.3.1 (2025-01-23 21:20), 3.3.3 (2025-02-12 00:50)

Other packages that cited Surrogate R package

View Surrogate citation profile

Other R packages that Surrogate depends, imports, suggests or enhances

View Surrogate dependency map

Complete documentation for Surrogate

View documentation PDF

Functions, R codes and Examples using the Surrogate R package

Some associated functions: AA.MultS . ARMD.MultS . ARMD . BifixedContCont . BimixedCbCContCont . BimixedContCont . Bootstrap.MEP.BinBin . CausalDiagramBinBin . CausalDiagramContCont . ECT . Fano.BinBin . FixedBinBinIT . FixedBinContIT . FixedContBinIT . FixedContContIT . FixedDiscrDiscrIT . ICA.BinBin.Grid.Full . ICA.BinBin.Grid.Sample.Uncert . ICA.BinBin.Grid.Sample . ICA.ContCont.MultS.MPC . ICA.ContCont.MultS.PC . ICA.ContCont.MultS . ICA.ContCont.Mult_alt . ICA.Sample.ContCont . ICABinBin . ICABinBinCounterAssum . ICABinCont . ICAContCont . ISTE.ContCont . LongToWide . MICA.Sample.ContCont . MICAContCont . MarginalProbs . MaxEntICABinBin . MaxEntICAContCont . MaxEntSPFBinBin . MinSurrContCont . MixedContContIT . Ovarian . PPE.BinBin . PROC.BinBin . Plot.FixedDiscrDiscrIT . Plot.PredTrialTContCont . Pos.Def.Matrices . Pred.TrialT.ContCont . Prentice . RandVec . Restrictions.BinBin . SPP.BinBin . SPP.BinCont . Schizo . Schizo_Bin . Schizo_BinCont . Schizo_PANSS . Sim.Data.Counterfactuals . Sim.Data.CounterfactualsBinBin . Sim.Data.MTS . Sim.Data.STS . Sim.Data.STSBinBin . Single.Trial.RE.AA . SurvSurv . Test.Mono . TrialLevelIT . TrialLevelMA . TwoStageSurvSurv . UnifixedContCont . UnimixedContCont . comb27.BinBin . fit_model_SurvSurv . ica_SurvSurv_sens . marginal_gof_scr . model_fit_measures . plot.CausalInference . plot.Fano.BinBin . plot.ICA.ContCont.Mult . plot.ICABinBin . plot.ICABinCont . plot.ISTE.ContCont . plot.InformationTheoretic . plot.InformationTheoreticBinCombn . plot.InformationTheoreticSurvSurv . plot.MaxEntContCont . plot.MaxEntICABinBin . plot.MaxEntSPFBinBin . plot.MetaAnalytic . plot.MinSurrContCont . plot.PPE.BinBin . plot.SPPBinBin . plot.SPPBinCont . plot.TrialLevelIT . plot.TrialLevelMA . plot.TwoStageSurvSurv . plot.comb27.BinBin . summary.gen .
Some associated R codes: AA.MultS.R . BifixedContCont.R . BimixedContCont.R . Bootstrap.MEP.BinBin.R . CausalDiagramBinBin.R . CausalDiagramContCont.R . CbC.R . Data.Processing.R . ECT.R . Fano.BinBin.R . FixedDiscrDiscrIT.R . ICA.BinBin.Grid.Full.R . ICA.BinBin.Grid.Sample.R . ICA.BinBin.Grid.Sample.Uncert.R . ICA.BinCont.R . ICA.Cont.Cont.MultS.R . ICA.Cont.Cont.MultS_alt.R . ICA.ContCont.MultS.MPC.R . ICA.ContCont.MultS.PC.R . ICA.Sample.ContCont.R . ICABinBin.R . ICABinBinCounterAssum.R . ICAContCont.R . ISTE.ContCont.R . LongToWide.R . MICA.Sample.ContCont.R . MICAContCont.R . MarginalProbs.R . MaxEntContCont.R . MaxEntICABinBin.R . MaxEntSPFBinBin.R . MinSurrContCont.R . MixedContContIT.R . PPE.BinBin.R . PROC.BinBin.R . Plot.FixedDiscrDiscrIT.R . Pos.Def.Matrices.R . Pred.TrialT.ContCont.R . Prentice.R . RandVec.R . Restrictions.BinBin.R . SPF.BinCont.R . SPP.BinBin.R . Sim.Data.Counterfactuals.R . Sim.Data.MTS.R . Sim.Data.STS.R . SimDataCounterfactualsBinBin.R . SimDataSTSBinBin.R . Single.Trial.RE.AA.R . Summary.SPF.BinCont.R . SummaryITContCont.R . SummaryMaxEntSPFBinBin.R . SummaryMetaAnalyticMTSContCont.R . SummaryMetaAnalyticSTSContCont.R . SummarySPPBinBin.R . SummaryTrialLevelMA.R . SurvSurv.R . Test.Mono.R . TrialLevelIT.R . TrialLevelMA.R . TwoStageSurvSurv.R . UnifixedContCont.R . UnimixedContCont.R . comb27.BinBin.R . fit_model_SurvSurv.R . goodness_of_fit_SurvSurv.R . log_likelihoods.R . plot.BinContCombnIT.R . plot.Fano.BinBin.R . plot.InfoTheoretic.R . plot.MaxEntContCont.R . plot.MaxEntSPF.BinBin.R . plot.MetaAnalyticMTS.R . plot.MetaAnalyticSTS.R . plot.PPE.BinBin.R . plot.SPPBinCont.R . plot.SurvSurv.R . plot.TrialLevelIT.R . plot.TrialLevelMA.R . plot.TwoStageSurvSurv.R . plot.comb27.BinBin.R . plot_ICABinBin.R . plot_ICABinCont.R . plot_MaxEntICABinBin.R . plot_SPPBinBin.R . sensitivity_analysis_SurvSurv.R . summary.Fano.BinBin.R . summary.FixedDIscrDiscrIT.R . summary.PPE.BinBin.R . summary.SurvSurv.R . summary.TrialLevelIT.R . summary.TwoStageSurvSurv.R . summaryBinContCombnIT.R . summary_ICABinBin.R . summary_ICABinCont.R . summary_MaxEntContCont.R . summary_MaxEntICABinBin.R . utils.R . Full Surrogate package functions and examples

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