In rare disease study, the failure rate is low in a large cohort of subjects due to constraint by funding and research time. Case-cohort design is a widely used sampling scheme for cost-effective study. The weighted pseudo-score (PS) estimators are proposed in the additive hazards model with data generated under case-cohort design. In this article, we present two more effective estimators: the generalized moment estimations with two different weights. Combining the subgroup information with the PS estimator, the generalized methods of moment are applied for the regression parameters. We establish the asymptotic properties of the proposed estimators and conclude that the estimators are more efficient than the weighted PS estimator. We also show the asymptotic properties for the estimated cumulative baseline hazard function. Simulation and real data studies demonstrate the finite-sample performances of the proposed method and the corresponding theories.

在稀有疾病研究中，由于资金和研究时间的限制，大批受试者的失败率很低。案例队列设计是用于成本效益研究的一种广泛使用的抽样方案。在加性危害模型中提出了加权伪分数（PS）估计量，并使用了案例队列设计生成的数据。在本文中，我们提出了两个更有效的估计器：具有两个不同权重的广义矩估计。将子组信息与PS估计量相结合，将广义矩量方法应用于回归参数。我们建立了拟议估计量的渐近性质，并得出结论，估计量比加权PS估计量更有效。我们还显示了估计的累积基线危害函数的渐近性质。