不规则观测的纵向数据的反向强度加权概括估计方程:在访问率模型中应包括哪些变量?
Eleanor M Pullenayegum1,2, Di Shan2
1The Hospital for Sick Children, 555 University Avenue, Toronto, ON M5G 1X8, Canada.
Biometrics
|October 8, 2025
概括
按访问率加权通用估计方程 (GEE) 提供了公正的回归估计. 包括结果预测器可以改善差异,而访问预测器可以增加或减少差异,需要仔细考虑.
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
背景情况:
- 纵向研究经常涉及不规则和有信息的访问时间.
- 一般估计方程 (GEE) 通常用于分析此类数据.
- 访问时间共变量对GEE差异估计的影响尚未完全理解.
研究的目的:
- 研究将额外的共变量纳入访问率模型对GEE回归系数方差的影响.
- 为纵向数据分析提供参观过程模型中选择共变量的建议.
主要方法:
- 该研究从理论上分析了将共变量添加到访问率模型对GEE变异的影响.
- 在条件独立性假设下检查回归系数估计的非对称性属性.
- 提出的方法应用于来自重大抑郁症研究的现实数据集.
主要成果:
- 添加与结果和访问过程无关的共变量不会改变GEE变量.
- 包括与结果相关的共变量,但不包括访问过程,可以降低GEE变量.
- 添加与访问过程相关的共变量,而不是结果,可以增加或减少GEE变量,这取决于共变量相关性.
结论:
- 访问过程模型应该包括与结果相关的变量.
- 与访问时间相关的共变量,但不是结果,应在GEE模型中谨慎使用.
- 在访问率模型中仔细选择共变量对于高效可靠的纵向数据分析至关重要.
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