A QUANTITATIVE STUDY OF THE BIAS IN ESTIMATING THE TREATMENT EFFECT CAUSED BY OMITTING A BALANCED COVARIATE IN SURVIVAL MODELS
A QUANTITATIVE STUDY OF THE BIAS IN ESTIMATING THE TREATMENT EFFECT CAUSED BY OMITTING A BALANCED COVARIATE IN SURVIVAL MODELS
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DOI：
10.1002/sim.4780071205
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发表时间：
1988-12-01
影响因子：
2
通讯作者：
PIANTADOSI, S
中科院分区：
文献类型：
--
作者：
CHASTANG, C;BYAR, D;PIANTADOSI, S
本文讨论了在生存模型中，当未能对平衡的预后变量进行调整时，治疗效果估计中的偏差的量化方面。文中给出了一个简单的数值算例，并给出了乘性指数生存模型中的近似计算公式。通过仿真验证了公式的准确性。此外，还给出了功率损失和省略一个以上预测协变量的影响的近似计算和模拟。本文还对威布尔模型和考克斯模型进行了模拟检验。对这种偏差的研究与许多应用工作有关，并表明，除非变量具有很强的预测性或数量很多，否则省略平衡协变量的影响可能是适度的。这项工作强调需要对调整后的和未调整的分析进行彻底的比较，以便合理地解释治疗效果。
This paper discusses the quantitative aspects of bias in estimates of treatment effect in survival models when there is failure to adjust on balanced prognostic variables. A simple numerical example of this basis is given along with approximate formulae for its calculation in the multiplicative exponential survival model. The accuracy of the formulae is checked by simulation. In addition, approximate calculations and simulations of power loss and the effects of omitting more than one prognostic covariate are present. The Weibull and Cox models are also examined using simulation. Study of this bias is pertinent to much applied work, and shows that the effect of omitting balanced covariates can be modest unless the variables are strongly prognostic or many in number. This work emphasizes the need for thorough comparisons of adjusted and unadjusted analyses for sensible interpretation of treatment effects.