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wintime (version 0.4.1)

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

166

Version

0.4.1

License

MIT + file LICENSE

Maintainer

James Troendle

Last Published

August 28th, 2025

Functions in wintime (0.4.1)

km

Fit a Kaplan-Meier model
getWintimeIntegral_rest

Win time difference with time restriction
getWintimeIntegral

Helper functions for package functions
setKM

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

Fit a Markov model
perm

Resample using permutations
wintime

Run a win time calculation
EWTP

Expected win time against trial population
EWTPR

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

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

Run composite analysis
RMT

Restricted mean survival in favor of treatment
RPWT

Time Restricted Pairwise win time
EWTR

Expected win time against reference
EWT

Expected win time
PWT

Pairwise win time
REWTP

Expected win time against trial population
setEventTimes

Created a sorted vector of event times
WTR

Win time ratio
RWTR

Restricted win time ratio
bootstrap

Resample using bootstraps