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WINS
View on CRAN: Click
here
Download and install WINS package within the R console
Install from CRAN:
install.packages("WINS")
Install from Github:
library("remotes")
install_github("cran/WINS")
Install by package version:
library("remotes")
install_version("WINS", "1.4.1")
Attach the package and use:
library("WINS")
Maintained by
Ying Cui
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-12-16
Latest Update: 2023-07-09
Description:
Calculate the win statistics (win ratio, net benefit and win odds) for prioritized multiple endpoints, plot the win statistics and win proportions over study time if at least one time-to-event endpoint is analyzed, and simulate datasets with dependent endpoints. The package can handle any type of outcomes (continuous, ordinal, binary, time-to-event) and allow users to perform stratified analysis, inverse probability of censoring weighting (IPCW) and inverse probability of treatment weighting (IPTW) analysis.
How to cite:
Ying Cui (2021). WINS: The R WINS Package. R package version 1.4.1, https://cran.r-project.org/web/packages/WINS
Previous versions and publish date:
Other packages that cited WINS R package
View WINS citation profile
Other R packages that WINS depends,
imports, suggests or enhances
Functions, R codes and Examples using
the WINS R package
Some associated functions: Z_t_con . Z_t_trt . data_binary . data_continuous . data_mix . data_mix_stratum . data_tte . partition_t.plot . sim.data . stat_t.plot . win.stat.Luo . win.stat . win.strategy.default .
Some associated R codes: covipcw.adjusted.KL.R . get.win.stat_t.R . globals.R . ipcw.adjusted.KL.R . original.KL.R . partition_t.plot.R . sim.data.R . stat_t.plot.R . win.stat.Luo.R . win.stat.R . win.strategy.default.R . Full WINS package functions and examples
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