Nonparametric and Cox-Based Estimation of ATE in Competing Risks

Estimation of average treatment effects (ATE) of two static treatment regimes on time-to-event outcomes with K competing events (K can be 1). The method uses propensity scores weighting for emulation of baseline randomization.


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install.packages("causalCmprsk")

1.0.1 by Bella Vakulenko-Lagun, 3 months ago


https://github.com/Bella2001/causalCmprsk


Report a bug at https://github.com/Bella2001/causalCmprsk/issues


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


Authors: Bella Vakulenko-Lagun , Colin Magdamo , Marie-Laure Charpignon , Bang Zheng , Mark Albers , Sudeshna Das


Documentation:   PDF Manual  


GPL (>= 2) license


Imports survival, inline, doParallel, parallel, utils, foreach, data.table, purrr

Suggests knitr, rmarkdown, bookdown, tidyverse, ggalt, cobalt, ggsci, modEvA, naniar, DT, Hmisc, hrbrthemes, summarytools, kableExtra


See at CRAN