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CauchyCP (version 0.1.1)

Powerful Test for Survival Data under Non-Proportional Hazards

Description

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.

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Version

Install

install.packages('CauchyCP')

Monthly Downloads

90

Version

0.1.1

License

GPL-2

Maintainer

Hong Zhang

Last Published

August 12th, 2022

Functions in CauchyCP (0.1.1)

CauchyCP

A robust test under non-proportional hazards using Cauchy combination of change-point Cox regressions.
gast

Example 1: gastric carcinoma trial data