Grant Shannon, Chen Ying Qing, May Susanne
University of Washington, Seattle, WA, USA.
Lifetime Data Anal. 2014 Jul;20(3):355-68. doi: 10.1007/s10985-013-9277-1. Epub 2013 Aug 9.
There are few readily-implemented tests for goodness-of-fit for the Cox proportional hazards model with time-varying covariates. Through simulations, we assess the power of tests by Cox (J R Stat Soc B (Methodol) 34(2):187-220, 1972), Grambsch and Therneau (Biometrika 81(3):515-526, 1994), and Lin et al. (Biometrics 62:803-812, 2006). Results show that power is highly variable depending on the time to violation of proportional hazards, the magnitude of the change in hazard ratio, and the direction of the change. Because these characteristics are unknown outside of simulation studies, none of the tests examined is expected to have high power in real applications. While all of these tests are theoretically interesting, they appear to be of limited practical value.
对于具有时变协变量的Cox比例风险模型,几乎没有易于实施的拟合优度检验。通过模拟,我们评估了Cox(《皇家统计学会会刊B辑(方法学)》34(2):187 - 220, 1972)、Grambsch和Therneau(《生物统计学》81(3):515 - 526, 1994)以及Lin等人(《生物统计学》62:803 - 812, 2006)所提出检验的功效。结果表明,功效高度可变,这取决于违背比例风险的时间、风险比变化的幅度以及变化的方向。由于这些特征在模拟研究之外是未知的,所以在实际应用中,所检验的任何一种检验都不太可能具有高功效。虽然所有这些检验在理论上都很有趣,但它们的实际价值似乎有限。