倾向权重加上对比例危险模型的调整不是两倍强大的
Erin E Gabriel1, Michael C Sachs1, Ingeborg Waernbaum2
1Section of Biostatistics, Department of Public Health, University of Copenhagen, København 1353, Denmark.
Biometrics
|July 22, 2024
概括
将考克斯模型与倾向性得分权重相结合,往往无法产生双重可靠的生存分析估计器,特别是当因果关系确实存在时. 新的方法为生存差异和完全生存曲线提供了可靠的估计.
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:
- 通常情况下,生存分析将考克斯模型和倾向性得分权重结合起来,以获得两倍可靠的估计.
- 这种方法旨在在Cox或倾向得分模型被正确指定时进行无偏的危险比率估计.
- 然而,当真正的因果关系存在时,这种组合往往无法达到双重强度.
研究的目的:
- 为了研究组合生存分析模型的双重稳定性.
- 为了证明当前方法在因果效应下实现双重稳定性的局限性.
- 为生存分析提出新的,双重可靠的估计器.
主要方法:
- 模拟研究使用半参数Cox,Weibull和灵活的参数比例危险模型进行.
- 分析了倾向性得分权重与比例危险生存模型的组合.
- 为生存差异和完全生存曲线开发了新的双倍强大的估计器.
主要成果:
- 倾向性得分权重和生存模型的组合通常不会在存在因果关系时产生双重可靠的估计器.
- 双重强度仅在没有因果效应的零假设下才被证明是有效的.
- 该研究为生存差异和整个生存曲线提供了替代的双倍强大的估计器.
结论:
- 在生存分析中的标准组合方法在存在因果关系时缺乏双重稳定性.
- 建议的替代估计器在特定的审查假设下提供有效的双倍可靠的估计.
- 为实施这些新的双倍可靠的估计方法,提供了R代码.
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