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. ).


News

survtmle 1.1.1

  • Minor bug fixes and documentation updates.

survtmle 1.1.0

  • Adds support for the use of speedglm to fit the numerous regressions fit in the estimation procedure. Users may see warnings when speedglm fails, in which case the code defaults back to standard glm.
  • Fixes problems with the plot.tp.survtmle method induced, by changes in the inner working of tidyr as of tidyr v0.8.0.
  • Adds a method confint.tp.survtmle that computes and provides output tables for statistical inference directly from objects of class tp.survtmle. This provides information equivalent to that output by confint.survtmle.

survtmle 1.0.0

  • The first public release made available on CRAN.

Reference manual

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install.packages("survtmle")

1.1.1 by David Benkeser, 3 months ago


https://github.com/benkeser/survtmle


Report a bug at https://github.com/benkeser/survtmle/issues


Browse source code at https://github.com/cran/survtmle


Authors: David Benkeser [aut, cre, cph] , Nima Hejazi [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Matrix, speedglm, SuperLearner, plyr, dplyr, tidyr, stringr, ggplot2, ggsci

Suggests testthat, knitr, rmarkdown, survival, cmprsk, tibble


See at CRAN