survtmle: Compute Targeted Minimum Loss-Based Estimates in Right-Censored Survival Settings

Targeted estimates of marginal cumulative incidence in survival settings with and without competing risks, including estimators that respect bounds (Benkeser, Carone, and Gilbert. Statistics in Medicine, 2017. <doi:10.1002/sim.7337>).

Version: 1.1.1
Depends: R (≥ 3.0.0)
Imports: Matrix, speedglm, SuperLearner, plyr, dplyr, tidyr (≥ 0.8.0), stringr, ggplot2, ggsci
Suggests: testthat, knitr, rmarkdown, survival, cmprsk, tibble
Published: 2019-04-16
Author: David Benkeser ORCID iD [aut, cre, cph], Nima Hejazi ORCID iD [aut]
Maintainer: David Benkeser <benkeser at emory.edu>
BugReports: https://github.com/benkeser/survtmle/issues
License: MIT + file LICENSE
URL: https://github.com/benkeser/survtmle
NeedsCompilation: no
Materials: NEWS
CRAN checks: survtmle results

Documentation:

Reference manual: survtmle.pdf
Vignettes: Targeted Learning for Survival Analysis with Competing Risks

Downloads:

Package source: survtmle_1.1.1.tar.gz
Windows binaries: r-devel: survtmle_1.1.1.zip, r-release: survtmle_1.1.1.zip, r-oldrel: survtmle_1.1.1.zip
macOS binaries: r-release (arm64): survtmle_1.1.1.tgz, r-oldrel (arm64): survtmle_1.1.1.tgz, r-release (x86_64): survtmle_1.1.1.tgz, r-oldrel (x86_64): survtmle_1.1.1.tgz
Old sources: survtmle archive

Linking:

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