CauchyCP: Powerful Test for Survival Data under Non-Proportional Hazards

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) <arXiv:2101.00059>. 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.

Getting started

Package details

AuthorHong Zhang
MaintainerHong Zhang <hzhang@wpi.edu>
LicenseGPL-2
Version0.1.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("CauchyCP")

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CauchyCP documentation built on Aug. 12, 2022, 9:05 a.m.