Accelerated life tests usually contain subsampling, which represents a restriction on randomization. The two-stage approach can deal with lifetime data from experiments with subsampling. However, this method did not introduce how to reduce the biases of estimators and compute confidence intervals of low percentiles. In this article, we build the model between percentile and stress factors, and obtain likelihood-based inference on percentile. In addition, we reduce the biases of estimators using an unbiasing factor method. Finally, we illustrate our method through a real example and compare with other methods via simulation study. The simulation results show that our proposed method is better in most cases.

加速寿命测试通常包含子采样，这代表了对随机化的限制。两阶段方法可以处理子采样实验中的生命周期数据。但是，该方法没有介绍如何减少估计量的偏差并计算低百分位数的置信区间。在本文中，我们建立了百分位数和压力因素之间的模型，并获得了基于似然性的百分位数推断。此外，我们使用无偏因子方法减少了估计量的偏倚。最后，我们通过一个真实的例子来说明我们的方法，并通过仿真研究与其他方法进行比较。仿真结果表明，本文提出的方法在大多数情况下效果更好。