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:
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