A brief conceptual tutorial of multilevel analysis in social epidemiology:: linking the statistical concept of clustering to the idea of contextual phenomenon
A brief conceptual tutorial of multilevel analysis in social epidemiology:: linking the statistical concept of clustering to the idea of contextual phenomenon
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DOI：
10.1136/jech.2004.023473
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发表时间：
2005-06-01
影响因子：
6.3
通讯作者：
Rästam, L
中科院分区：
文献类型：
--
作者：
Merlo, J;Chaix, B;Rästam, L
研究目的：这篇教学文章是针对读者倾向于接近多级回归分析（MLRA）在一个更概念化的方式比数学。然而，它专门开发了一个流行病学的多层次分析，特别强调健康变化的措施（例如，组内相关性）。在调查健康的背景决定因素时，与更传统的关联措施（例如，回归系数）相比，这些措施在文献中使用不足。提供了一个链接，这将是可以理解的流行病学家，MLRA和社会流行病学的概念之间，特别是聚类的统计思想和概念之间的上下文phenomenon.Design和participants：该研究使用了一个例子的基础上假设的数据收缩压（SBP）从25 000人生活在39个街区。由于重点是空MLRA模型，因此该研究不使用任何自变量，而是主要关注人与人之间和社区之间的SBP方差。组内相关（ICC = 0.08）被告知在社区内个体SBP的明显聚集，显示8% SBP的总个体差异发生在邻里水平，可能归因于背景邻里因素或结论：聚类的统计思想出现适当的量化“上下文现象”，这是在社会流行病学的核心相关性。这两个概念都表明，在健康结果变量方面，来自同一社区的人比来自不同社区的人更相似。
Study objective: This didactical essay is directed to readers disposed to approach multilevel regression analysis (MLRA) in a more conceptual than mathematical way. However, it specifically develops an epidemiological vision on multilevel analysis with particular emphasis on measures of health variation ( for example, intraclass correlation). Such measures have been underused in the literature as compared with more traditional measures of association ( for example, regression coefficients) in the investigation of contextual determinants of health. A link is provided, which will be comprehensible to epidemiologists, between MLRA and social epidemiological concepts, particularly between the statistical idea of clustering and the concept of contextual phenomenon.Design and participants: The study uses an example based on hypothetical data on systolic blood pressure (SBP) from 25 000 people living in 39 neighbourhoods. As the focus is on the empty MLRA model, the study does not use any independent variable but focuses mainly on SBP variance between people and between neighbourhoods.Results: The intraclass correlation (ICC = 0.08) informed of an appreciable clustering of individual SBP within the neighbourhoods, showing that 8% of the total individual differences in SBP occurred at the neighbourhood level and might be attributable to contextual neighbourhood factors or to the different composition of neighbourhoods.Conclusions: The statistical idea of clustering emerges as appropriate for quantifying "contextual phenomena'' that is of central relevance in social epidemiology. Both concepts convey that people from the same neighbourhood are more similar to each other than to people from different neighbourhoods with respect to the health outcome variable.