Gilbert Peter B, Sun Yanqing
Department of Biostatistics, University of Washington and Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Department of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA.
J R Stat Soc Ser C Appl Stat. 2015 Jan 1;64(1):49-73. doi: 10.1111/rssc.12067.
This article develops hypothesis testing procedures for the stratified mark-specific proportional hazards model in the presence of missing marks. The motivating application is preventive HIV vaccine efficacy trials, where the mark is the genetic distance of an infecting HIV sequence to an HIV sequence represented inside the vaccine. The test statistics are constructed based on two-stage efficient estimators, which utilize auxiliary predictors of the missing marks. The asymptotic properties and finite-sample performances of the testing procedures are investigated, demonstrating double-robustness and effectiveness of the predictive auxiliaries to recover efficiency. The methods are applied to the RV144 vaccine trial.
本文针对存在缺失标记情况下的分层标记特定比例风险模型，开发了假设检验程序。其动机应用是预防性HIV疫苗疗效试验，其中标记是感染的HIV序列与疫苗中所代表的HIV序列的遗传距离。检验统计量基于两阶段有效估计量构建，该估计量利用了缺失标记的辅助预测变量。研究了检验程序的渐近性质和有限样本性能，证明了预测辅助变量在恢复效率方面的双重稳健性和有效性。这些方法应用于RV144疫苗试验。
