TxEffectsSurvival: Treatment Effect Inference for Terminal and Non-Terminal Events
under Competing Risks
Provides several confidence interval and testing procedures, based on either
semiparametric (using event-specific win ratios) or nonparametric measures,
including the ratio of integrated cumulative hazard (RICH) and the ratio of
integrated transformed cumulative hazard (RITCH), for treatment effect inference
with terminal and non-terminal events under competing risks. The semiparametric
results were developed in Yang et al. (2022 <doi:10.1002/sim.9266>), and the
nonparametric results were developed in Yang (2025 <doi:10.1002/sim.70205>).
For comparison, results for the win ratio (Finkelstein and Schoenfeld 1999
<doi:10.1002/(SICI)1097-0258(19990615)18:11%3C1341::AID-SIM129%3E3.0.CO;2-7>),
Pocock et al. 2012 <doi:10.1093/eurheartj/ehr352>, and Bebu and Lachin 2016
<doi:10.1093/biostatistics/kxv032>) are included. The package also supports
univariate survival analysis with a single event. In this package, effect size
estimates and confidence intervals are obtained for each event type, and several
testing procedures are implemented for the global null hypothesis of no treatment
effect on either terminal or non-terminal events. Furthermore, a test of proportional
hazards assumptions, under which the event-specific win ratios converge to hazard
ratios, and a test of equal hazard ratios, are provided. For summarizing the treatment
effect across all events, confidence intervals for linear combinations of the
event-specific win ratios, RICH, or RITCH are available using pre-determined or
data-driven weights. Asymptotic properties of these inference procedures are
discussed in Yang et al. (2022 <doi:10.1002/sim.9266>) and Yang (2025
<doi:10.1002/sim.70205>).
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