Zhang Zhigang, Sun Jianguo, Sun Liuquan
Department of Statistics, Oklahoma State University, 301 Mathematics Sciences Building, Stillwater, OK 74074, USA.
Stat Med. 2005 May 15;24(9):1399-407. doi: 10.1002/sim.2001.
Current status data arise when each study subject is observed only once and the survival time of interest is known only to be either less or greater than the observation time. Such data often occur in, for example, cross-sectional studies, demographical investigations and tumorigenicity experiments and several semi-parametric and non-parametric methods for their analysis have been proposed. However, most of these methods deal only with the situation where observation time is independent of the underlying survival time completely or given covariates. This paper discusses regression analysis of current status data when the observation time may be related to the underlying survival time and inference procedures are presented for estimation of regression parameters under the additive hazards regression model. The procedures can be easily implemented and are applied to two motivating examples.
当每个研究对象仅被观察一次，且感兴趣的生存时间仅已知小于或大于观察时间时，就会产生当前状态数据。例如，此类数据常出现在横断面研究、人口调查和致瘤性实验中，并且已经提出了几种用于分析它们的半参数和非参数方法。然而，这些方法大多仅处理观察时间与潜在生存时间完全独立或给定协变量的情况。本文讨论了观察时间可能与潜在生存时间相关时当前状态数据的回归分析，并给出了在加法风险回归模型下估计回归参数的推断程序。这些程序易于实现，并应用于两个激励性示例。
