Department of Epidemiology and Biostatistics, University of Georgia, Athens, Georgia, USA.
Stat Med. 2023 Sep 30;42(22):4043-4055. doi: 10.1002/sim.9847. Epub 2023 Jul 13.
We consider the semiparametric accelerated failure time (AFT) model with multiple covariates measured with error. Existing methods for the AFT model are either inconsistent, computationally intensive, or require stringent assumptions. To overcome these limitations, we develop a correction approach for a general smooth function of error-contaminated variables. We apply this method to the smoothed rank-based score function for the AFT model. The estimator is consistent and asymptotically normal. The finite-sample performance of the method is assessed by simulation studies. The approach is illustrated by application to data from an HIV clinical trial.
我们考虑了具有多个协变量的半参数加速失效时间 (AFT) 模型，这些协变量存在测量误差。现有的 AFT 模型方法要么不一致，计算密集，要么需要严格的假设。为了克服这些限制，我们为一般的误差污染变量的平滑函数开发了一种校正方法。我们将此方法应用于 AFT 模型的平滑秩分函数。该估计量是一致的和渐近正态的。通过模拟研究评估了该方法的有限样本性能。该方法通过对 HIV 临床试验数据的应用来说明。
