Effect of covariate omission in Weibull accelerated failure time model: A caution
Effect of covariate omission in Weibull accelerated failure time model: A caution
复制标题
威布尔加速失效时间模型中协变量遗漏的影响：警告
DOI：
10.1002/bimj.201300006
复制
发表时间：
2014
影响因子：
1.7
通讯作者：
Yasunori Sato
中科院分区：
文献类型：
--
作者：
M. Gosho;K. Maruo;Yasunori Sato
加速失效时间模型作为一种替代比例风险模型在生存数据的分析。我们研究协变量遗漏的情况下，应用威布尔加速失效时间模型的影响。在未删失设置中，当省略重要协变量时，治疗效应的渐近偏倚理论上为零;然而，治疗效应的渐近方差估计量可能存在偏倚，然后治疗效应的Wald检验的大小可能超过标称水平。在某些情况下，测试规模可能是标称水平的两倍以上。在一项模拟研究中，在删失和未删失设置中，当省略预后协变量时，治疗效应检验的I类错误可能会扩大。这项工作备注的粗心使用的加速失效时间模型。我们建议使用稳健的三明治方差估计，以避免在加速失效时间模型中的I型错误的膨胀，虽然稳健的方差是不常用的生存数据分析。
The accelerated failure time model is presented as an alternative to the proportional hazard model in the analysis of survival data. We investigate the effect of covariates omission in the case of applying a Weibull accelerated failure time model. In an uncensored setting, the asymptotic bias of the treatment effect is theoretically zero when important covariates are omitted; however, the asymptotic variance estimator of the treatment effect could be biased and then the size of the Wald test for the treatment effect is likely to exceed the nominal level. In some cases, the test size could be more than twice the nominal level. In a simulation study, in both censored and uncensored settings, Type I error for the test of the treatment effect was likely inflated when the prognostic covariates are omitted. This work remarks the careless use of the accelerated failure time model. We recommend the use of the robust sandwich variance estimator in order to avoid the inflation of the Type I error in the accelerated failure time model, although the robust variance is not commonly used in the survival data analyses.