无与伦比的空间分层控制:一个模拟研究,使用空间多样化的控制和通用添加模型检查效率和精度
Ian W Tang1, Scott M Bartell2, Verónica M Vieira1
1Department of Environmental and Occupational Health, Program in Public Health, Susan and Henry Samueli College of Health Sciences, University of California, 100 Theory Drive, Suite 100, Irvine, CA 92617, USA.
Spatial and spatio-temporal epidemiology
|June 10, 2023
概括
空间分层随机抽样 (SSRS) 改善了对空间分析的对照选择. 与简单的随机抽样相比,这种方法提供了更高的效率和更一致的结果,特别是在人口密度较低的地区.
科学领域:
- 流行病学 流行病学
- 地理信息系统 (GIS) 是指地理信息系统.
- 生物统计学 生物统计学
背景情况:
- 流行病学中的空间分析通常依赖于对照选择方法.
- 传统的方法,如简单的随机抽样 (SRS),可能无法充分代表地理分布.
- 有效的控制选择对于准确的空间流行病学研究至关重要.
研究的目的:
- 评估空间分层随机抽样 (SSRS) 的性能,用于在空间分析中选择对照.
- 将SSRS与简单的随机抽样 (SRS) 进行比较,使用马萨诸塞州早产病例研究.
- 评估SSRS对统计模型准确性和效率的影响.
主要方法:
- 通过将研究区域划分为空间层并从每个层内的非案例中选择对照来开发和应用SSRS.
- 进行了模拟研究,适应了使用SSRS和SRS选择的对照的通用添加模型.
- 与使用所有非案例的模型比较平均二次误差 (MSE),相对效率 (RE),偏差和映射结果.
主要成果:
- 与SRS设计 (0.0072-0.0073) 相比,SSRS设计显示了较低的平均平均平方误差 (0.0042-0.0044).
- SSRS实现了比SRS (71%) 更高的相对效率 (77-80%).
- SSRS在模拟中产生了更一致的统计显著地图结果,特别是在人口密度较低的地区.
结论:
- 与SRS相比,SSRS是在空间分析中选择控制的更有效,更可靠的方法.
- 由于SSRS的地理平衡性质,可以提高模型性能和空间模式检测.
- 在不同地理环境的空间流行病学研究中,SSRS特别有利.
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