Package: SurvCorr 1.1

SurvCorr: Correlation of Bivariate Survival Times

Estimates correlation coefficients with associated confidence limits for bivariate, partially censored survival times. Uses the iterative multiple imputation approach proposed by Schemper, Kaider, Wakounig and Heinze (2013) <doi:10.1002/sim.5874>. Provides a scatterplot function to visualize the bivariate distribution, either on the original time scale or as copula.

Authors:Georg Heinze [aut, cre], Meinhard Ploner [aut], Alexandra Kaider [aut], Gregor Steiner [aut]

SurvCorr_1.1.tar.gz
SurvCorr_1.1.zip(r-4.5)SurvCorr_1.1.zip(r-4.4)SurvCorr_1.1.zip(r-4.3)
SurvCorr_1.1.tgz(r-4.5-any)SurvCorr_1.1.tgz(r-4.4-any)SurvCorr_1.1.tgz(r-4.3-any)
SurvCorr_1.1.tar.gz(r-4.5-noble)SurvCorr_1.1.tar.gz(r-4.4-noble)
SurvCorr_1.1.tgz(r-4.4-emscripten)SurvCorr_1.1.tgz(r-4.3-emscripten)
SurvCorr.pdf |SurvCorr.html✨
SurvCorr/json (API)

# Install 'SurvCorr' in R:
install.packages('SurvCorr', repos = c('https://georgheinze.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/georgheinze/survcorr/issues

Datasets:

On CRAN:

Conda:

2.70 score 2 scripts 166 downloads 2 exports 9 dependencies

Last updated 2 years agofrom:5bd49ed43c. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 14 2025
R-4.5-winOKMar 14 2025
R-4.5-macOKMar 14 2025
R-4.5-linuxOKMar 14 2025
R-4.4-winOKMar 14 2025
R-4.4-macOKMar 14 2025
R-4.4-linuxOKMar 14 2025
R-4.3-winOKMar 14 2025
R-4.3-macOKMar 14 2025

Exports:Survsurvcorr

Dependencies:dotCall64fieldslatticemapsMatrixRcppspamsurvivalviridisLite