两个阶段还是没有两个阶段? 这是IPD元分析项目的问题
Richard D Riley1, Joie Ensor1, Miriam Hattle1,2
1Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK.
Research synthesis methods
|August 22, 2023
概括
个人参与者数据元分析 (IPDMA) 需要在一阶段和两阶段方法之间进行选择. 对于小型研究来说,一个阶段的方法是首选的,而对于大多数研究人员来说,两个阶段的方法通常是足够的.
科学领域:
- 生物统计学 生物统计学
- 流行病学 流行病学
- 医学研究综合 医学研究综合
背景情况:
- 个人参与者数据元分析 (IPDMA) 涉及从多项研究中合成原始数据.
- 研究人员面临两种主要分析方法之间的选择:两阶段和一阶段的元分析.
- 最优的方法是研究界正在进行的辩论的主题.
研究的目的:
- 为IPDMA项目提供明确的指导,以便在一阶段和两阶段的元分析方法之间进行选择.
- 澄清关于一阶段方法普遍优越性的常见误解.
- 帮助研究人员根据研究特征做出明智的决策.
主要方法:
- 两阶段的方法包括分析个别研究数据以获得总计估计,然后进行标准的元分析.
- 一阶段方法同时使用混合效应模型分析所有单个参与者数据,以考虑聚类和异质性.
- 根据研究规模和事件数量等因素提供指导.
主要成果:
- 对于IPDMA项目来说,建议采用一阶段方法,因为大多数组成研究都很小,因为它更准确的可能性.
- 对于其他情况,只要遵循最佳实践,可以使用一阶段或两阶段的方法.
- 这两种方法之间的结果差异往往来自于建模假设或估计技术的变化,而不是阶段数量本身.
结论:
- 一阶段和两阶段的方法都是IPDMA中有价值的工具,而这两种方法都不是通用的解决方案.
- 仅主张单阶段方法的说法是误导性的;双阶段方法仍然是一个有效的,经常足够的选择.
- 仔细考虑研究特征和方法选择对于强大的IPDMA至关重要.
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