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).