双嵌套案例控制设计的绝对风险:因果特定的比例危险模型,带有和没有增强估计方程
Minjung Lee1, Mitchell H Gail2
1Department of Statistics, Kangwon National University, Chuncheon, Gangwon 24341, South Korea.
Biometrics
|July 12, 2024
概括
本研究介绍了在双嵌套病例控制 (DNCC) 研究中分析竞争风险的增强方法. 增强估计器提高了在复杂的生存数据中估计绝对风险和相对危险的效率.
科学领域:
- 生物统计学 生物统计学
- 流行病学 流行病学
- 生存分析的分析.
背景情况:
- 竞争的风险在生存分析中带来了挑战.
- 双嵌套病例控制 (DNCC) 设计提供高效的数据收集,但需要专门的估计方法.
- 准确估计绝对风险和相对危险对于了解疾病进展和结果至关重要.
研究的目的:
- 开发和验证使用DNCC数据的因果特定比例危险模型的高效估计器.
- 在存在竞争性风险的情况下,改进绝对风险和相对风险的估计.
- 为了利用来自第二阶段样本的完整共变量数据和来自全队列的部分数据.
主要方法:
- 使用基于DNCC数据的反向采样概率的设计加权估计器.
- 增强标准估计器与一个术语,以纳入额外的队列数据,提高效率.
- 建立了对称性属性,并为拟议的方法推导了一致的方差估计器.
- 进行模拟,以评估实际样本大小的估计器的性能.
主要成果:
- 与标准设计加权估计器相比,增强的设计加权估计器显示出更高的效率.
- 拟议的非对称方法在模拟中显示了名义操作特性.
- 使用前列腺,肺部,结肠直肠和卵巢癌查试验的真实数据验证了方法.
结论:
- 开发的增强估计器为分析DNCC研究中的竞争风险提供了更有效的方法.
- 这些方法是稳固的,适合在流行病学研究中的实际应用.
- 准确估计绝对风险和相对危险是可以通过提出的技术实现的.
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