ABSTRACT

Recent studies show that medical cost data can be heavily censored and highly skewed, which leads to have more complex cost data analysis. In this paper, we propose influence function and empirical likelihood (EL)-based methods to construct confidence regions for regression parameters in median cost regression models with censored data. We further propose confidence intervals for the median cost with given covariates using the proposed EL-based confidence regions. Simulation studies are conducted to compare the proposed EL-based confidence regions with the existing normal approximation-based confidence regions in terms of coverage probabilities. The new EL-based methods are observed to have better finite sample performances than existing methods particularly when the censoring proportion is high. The new methods are also illustrated through a real data example.

摘要

最近的研究表明，医疗成本数据可能会受到严重审查和高度偏斜，从而导致成本数据分析更加复杂。在本文中，我们提出了基于影响函数和经验似然 (EL) 的方法来为具有删失数据的中值成本回归模型中的回归参数构建置信区域。我们使用建议的基于 EL 的置信区域进一步提出了具有给定协变量的中值成本的置信区间。进行模拟研究以在覆盖概率方面比较所提出的基于 EL 的置信区域与现有的基于正态近似的置信区域。观察到新的基于 EL 的方法比现有方法具有更好的有限样本性能，特别是当审查比例很高时。