# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "CauchyCP" in publications use:' type: software license: GPL-2.0-only title: 'CauchyCP: Powerful Test for Survival Data under Non-Proportional Hazards' version: 0.1.1 doi: 10.32614/CRAN.package.CauchyCP abstract: An omnibus test of change-point Cox regression models to improve the statistical power of detecting signals of non-proportional hazards patterns. The technical details can be found in Hong Zhang, Qing Li, Devan Mehrotra and Judong Shen (2021) . Extensive simulation studies demonstrate that, compared to existing tests under non-proportional hazards, the proposed CauchyCP test 1) controls the type I error better at small alpha levels; 2) increases the power of detecting time-varying effects; and 3) is more computationally efficient. authors: - family-names: Zhang given-names: Hong email: hzhang@wpi.edu repository: https://cranhaven.r-universe.dev commit: e420cffd910cd6896d912b4980d69e84f17990c9 date-released: '2022-08-12' contact: - family-names: Zhang given-names: Hong email: hzhang@wpi.edu