对多变量面板计数数据的比例率模型
Yangjianchen Xu1, Donglin Zeng1, Dan-Yu Lin1
1Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, United States.
Biometrics
|February 16, 2024
概括
本研究引入了一种新的统计方法,用于分析面板计数数据中的多重重复事件. 该方法有效地模拟共变量效应而不指定事件依赖性,为复杂的健康研究提供可靠的参数估计和模型检查.
科学领域:
- 生物统计学 生物统计学
- 流行病学 流行病学
- 统计建模 统计建模
背景情况:
- 多变量面板计数数据涉及每个受试者的多个重复事件类型.
- 分析这些数据需要处理复杂事件依赖和时间变化的协变量的方法.
研究的目的:
- 开发一个灵活的统计框架来分析多变量反复事件数据.
- 模拟时间依赖的共变量对多种事件类型的影响,同时不指定事件依赖性.
主要方法:
- 针对多个反复发生的事件,制定了比例率模型.
- 在独立性假设下使用非参数最大伪概率估计.
- 为参数估计开发了一个稳定的EM型算法.
主要成果:
- 实现了回归参数的一致和异常正常估计.
- 一个三明治估计器提供一致的协差矩阵估计.
- 开发了用于模型充分性检查的图形和数值方法.
结论:
- 拟议的方法为分析多变量面板计数数据提供了可靠的方法.
- 这些方法通过模拟研究和皮肤癌临床试验分析来验证.
- 这一框架有助于更深入地了解健康研究中反复发生的事件过程.
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