| surrosurv-package {surrosurv} | R Documentation |
Evaluation of Failure Time Surrogate Endpoints in Individual Patient Data Meta-Analyses
Description
Provides functions for the evaluation of surrogate endpoints when both the surrogate and the true endpoint are failure time variables. The approaches implemented are: (1) the two-step approach (Burzykowski et al, 2001) <DOI:10.1111/1467-9876.00244> with a copula model (Clayton, Plackett, Hougaard) at the first step and either a linear regression of log-hazard ratios at the second step (either adjusted or not for measurement error); (2) mixed proportional hazard models estimated via mixed Poisson GLM (Rotolo et al, 2017 <DOI:10.1177/0962280217718582>).
Details
The DESCRIPTION file:
| Package: | surrosurv |
| Type: | Package |
| Title: | Evaluation of Failure Time Surrogate Endpoints in Individual Patient Data Meta-Analyses |
| Version: | 1.1.26 |
| Authors@R: | c( person("Federico", "Rotolo", role="aut", email="federico.rotolo@gustaveroussy.fr", comment = c(ORCID = "0000-0003-4837-6501")), person("Xavier", "Paoletti", role="ctb"), person("Marc", "Buyse", role="ctb"), person("Tomasz", "Burzykowski", role="ctb"), person("Stefan", "Michiels", role="ctb", email="stefan.michiels@gustaveroussy.fr", comment = c(ORCID = "0000-0002-6963-2968")), person("Dan", "Chaltiel", role="cre", email="dan.chaltiel@gustaveroussy.fr", comment = c(ORCID = "0000-0003-3488-779X"))) |
| Maintainer: | Dan Chaltiel <dan.chaltiel@gustaveroussy.fr> |
| Description: | Provides functions for the evaluation of surrogate endpoints when both the surrogate and the true endpoint are failure time variables. The approaches implemented are: (1) the two-step approach (Burzykowski et al, 2001) <DOI:10.1111/1467-9876.00244> with a copula model (Clayton, Plackett, Hougaard) at the first step and either a linear regression of log-hazard ratios at the second step (either adjusted or not for measurement error); (2) mixed proportional hazard models estimated via mixed Poisson GLM (Rotolo et al, 2017 <DOI:10.1177/0962280217718582>). |
| Depends: | R (>= 3.5.0) |
| Imports: | copula, eha, grDevices, lme4, MASS, Matrix, msm, mvmeta, optimx, parallel, parfm, stats, survival |
| License: | GPL-2 |
| URL: | https://github.com/Oncostat/surrosurv |
| BugReports: | https://github.com/Oncostat/surrosurv/issues/ |
| VignetteBuilder: | R.rsp |
| Suggests: | R.rsp, testthat (>= 3.0.0) |
| Encoding: | UTF-8 |
| Config/testthat/edition: | 3 |
| Author: | Federico Rotolo [aut] (<https://orcid.org/0000-0003-4837-6501>), Xavier Paoletti [ctb], Marc Buyse [ctb], Tomasz Burzykowski [ctb], Stefan Michiels [ctb] (<https://orcid.org/0000-0002-6963-2968>), Dan Chaltiel [cre] (<https://orcid.org/0000-0003-3488-779X>) |
Index of help topics:
convergence Assesses the convergence of fitted models for
surrogacy evaluation
gastadj Individual data from the adjuvant GASTRIC
meta-analysis
gastadv Individual data from the advanced GASTRIC
meta-analysis
loocv Leave-one-trial-out cross-validation for
treatment effect prediction
poissonize Transform survival data for fitting a Poisson
model
simData.re Generate survival times for two endpoints in a
meta-analysis of randomized trials
ste Surrogate threshold effect
surrosurv Fit and print the models for evaluating the
surrogacy strength of a candidate surrogate
endpoint
surrosurv-package Evaluation of Failure Time Surrogate Endpoints
in Individual Patient Data Meta-Analyses
Author(s)
NA
Maintainer: Dan Chaltiel <dan.chaltiel@gustaveroussy.fr>
References
Rotolo F, Paoletti X, Burzykowski T, Buyse M, Michiels S. A Poisson approach for the validation of failure time surrogate endpoints in individual patient data meta-analyses. Statistical Methods in Medical Research 2017; In Press. doi: 10.1177/0962280217718582
Burzykowski T, Molenberghs G, Buyse M et al. Validation of surrogate end points in multiple randomized clinical trials with failure time end points. Journal of the Royal Statistical Society C 2001; 50:405–422. doi: 10.1111/1467-9876.00244
Gasparrini A, Armstrong B, Kenward MG. Multivariate meta-analysis for non-linear and other multi-parameter associations. Statistics in Medicine 2012; 31:3821–39. doi: 10.1002/sim.5471
Burzykowski T, Molenberghs G, Buyse M (2005). The Evaluation of Surrogate Endpoints. Springer, New York. https://rd.springer.com/book/10.1007/b138566