Song Xiao, Ma Shuangge
Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA 30602, USA.
Stat Med. 2008 Jul 20;27(16):3178-90. doi: 10.1002/sim.3156.
There has been substantial effort devoted to the analysis of censored failure time with covariates that are subject to measurement error. Previous studies have focused on right-censored survival data, but interval-censored survival data with covariate measurement error are yet to be investigated. Our study is partly motivated by analysis of the HIV clinical trial AIDS Clinical Trial Group (ACTG) 175 data, where the occurrence time of AIDS is interval censored and the covariate CD4 count is subject to measurement error. We assume that the data are realized from a proportional hazards model. A multiple augmentation approach is proposed to convert interval-censored data to right-censored data, and the conditional score approach is then employed to account for measurement error. The proposed approach is easy to implement and can be readily extended to other semiparametric models. Extensive simulations show that the proposed approach has satisfactory finite-sample performance. The ACTG 175 data are then analyzed.
针对带有测量误差协变量的删失失效时间分析，已经投入了大量精力。以往的研究主要集中在右删失生存数据上，但对于带有协变量测量误差的区间删失生存数据尚未进行研究。我们的研究部分是受艾滋病临床试验组（ACTG）175数据的分析启发，在该数据中，艾滋病的发生时间是区间删失的，且协变量CD4计数存在测量误差。我们假设数据是由比例风险模型生成的。提出了一种多重扩充方法，将区间删失数据转换为右删失数据，然后采用条件得分方法来处理测量误差。所提出的方法易于实施，并且可以很容易地扩展到其他半参数模型。大量模拟表明，所提出的方法具有令人满意的有限样本性能。随后对ACTG 175数据进行了分析。
