层次/多层次模型的应用和报告质量 (2010-2020年):系统性审查
Killian Asampana Asosega1,2, Atinuke Olusola Adebanji1, Eric Nimako Aidoo1
1Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
多层次模型越来越多地被使用,因为有层次数据. 报告类内相关性,估计和变量选择需要改进,以提高研究中的应用质量.
科学领域:
- 统计建模的多学科应用.
- 专注于层次和集群数据结构.
背景情况:
- 多级模型 (MLM) 由于数据层次结构,在各个学科中被广泛采用.
- 本次审查审查了MLMs结果的应用和报告.
研究的目的:
- 系统地审查采用和应用多层模型的情况.
- 评估MLM应用程序结果的报告质量.
主要方法:
- 在谷歌学者 (2010-2020) 上进行系统的文献搜索.
- 关键词:"多级模型"",层次的线性模型"",具有层次的混合模型".
- 纳入标准集中在MLM应用程序上,不包括软件开发.
主要成果:
- 审查了65篇文章,主要涉及健康/流行病学 (46.2%),教育/心理学 (15.4%) 和社会科学 (16.9%).
- 大多数研究使用了双层 (78.5%),横截面 (83.1%) 设计,且反应不变.
- 报告内容各不相同:类内相关性 (55.4%),估计方法 (58.5%),模型验证 (70.8%) 和软件 (90.8%).
结论:
- 由层次数据结构驱动的MLM使用率增加.
- 需要改进的领域包括报告类内相关性,参数估计和变量选择.
- 未来的研究应该探索将空间效应整合到MLM中.
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