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.

Version:	0.1.1
Imports:	stats, survival
Published:	2022-08-12
Author:	Hong Zhang
Maintainer:	Hong Zhang <hzhang at wpi.edu>
License:	GPL-2
NeedsCompilation:	no
CRAN checks:	CauchyCP results

Documentation:

Reference manual:

CauchyCP.pdf

Downloads:

Package source:	CauchyCP_0.1.1.tar.gz
Windows binaries:	r-devel: CauchyCP_0.1.1.zip, r-release: CauchyCP_0.1.1.zip, r-oldrel: CauchyCP_0.1.1.zip
macOS binaries:	r-release (arm64): CauchyCP_0.1.1.tgz, r-oldrel (arm64): CauchyCP_0.1.1.tgz, r-release (x86_64): CauchyCP_0.1.1.tgz, r-oldrel (x86_64): CauchyCP_0.1.1.tgz
Old sources:	CauchyCP archive

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