对于具有终端事件的纵向数据的双变时变系数模型的核心估计
Yue Wang1, Bin Nan1, John D Kalbfleisch2
1Department of Statistics, University of California, Irvine.
Journal of the American Statistical Association
|August 26, 2024
概括
我们开发了一种新的统计模型,用于分析终端事件患者数据. 这种非参数双变量时变系数模型通过考虑随访和剩余寿命来提高准确性.
科学领域:
- 生物统计学 生物统计学
- 纵向数据分析 纵向数据分析
- 生存分析的分析.
背景情况:
- 有终端事件的纵向数据带来了独特的分析挑战.
- 当前的参数模型在处理复杂的共同变量效应时,可能会出现错误的规范.
- 正确审查的数据需要专门的统计方法.
研究的目的:
- 提出一个灵活的非参数双变量时变系数模型.
- 通过避免对终端事件时间的假设来扩展现有方法.
- 为了准确地捕捉随访和剩余寿命的共同变量效应.
主要方法:
- 使用内核光滑方法来估计时间变化的回归系数.
- 采用交叉验证来进行最佳带宽选择.
- 应用底层平滑以减轻内核估计中的非对称偏差.
主要成果:
- 证明了内核估计趋于有限维正常分布.
- 开发了一个易于计算的三明治共变矩阵估计器.
- 模拟研究证实了拟议方法的理想性能.
结论:
- 拟议的非参数模型为参数方法提供了一个强大的替代方案.
- 该方法有效处理端末事件和审查的纵向数据.
- 成功应用于分析末期病患者的医疗费用.
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