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wintime (version 0.4.3)

Win Time Methods for Time-to-Event Data in Clinical Trials

Description

Performs an analysis of time-to-event clinical trial data using various "win time" methods, including 'ewt', 'ewtr', 'rmt', 'ewtp', 'rewtp', 'ewtpr', 'rewtpr', 'max', 'wtr', 'rwtr', 'pwt', and 'rpwt'. These methods are used to calculate and compare treatment effects on ordered composite endpoints. The package handles event times, event indicators, and treatment arm indicators and supports calculations on observed and resampled data. Detailed explanations of each method and usage examples are provided in "Use of win time for ordered composite endpoints in clinical trials," by Troendle et al. (2024). For more information, see the package documentation or the vignette titled "Introduction to wintime."

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Version

Install

install.packages('wintime')

Monthly Downloads

209

Version

0.4.3

License

MIT + file LICENSE

Maintainer

James Troendle

Last Published

January 28th, 2026

Functions in wintime (0.4.3)

setKM

Set event times and indicators used in the Kaplan-Meier survival curve calculation
wintime

Run a win time calculation
COMP

Run composite analysis
REWTP

Expected win time against trial population
REWTPR

Time Restricted Expected win time against trial population With redistribution to the right
RMT

Restricted mean survival in favor of treatment
EWTR

Expected win time against reference
EWTP

Expected win time against trial population
EWT

Expected win time
PWT

Pairwise win time
RPWT

Time Restricted Pairwise win time
EWTPR

Expected win time against trial population With redistribution to the right
markov

Fit a Markov model
setEventTimes

Created a sorted vector of event times
perm

Resample using permutations
getWintimeIntegral_rest

Win time difference with time restriction
RWTR

Restricted win time ratio
getWintimeIntegral

Helper functions for package functions
bootstrap

Resample using bootstraps
km

Fit a Kaplan-Meier model
WTR

Win time ratio