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A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena

机译:社会流行病学中多层次分析的简要概念教程:在多层次逻辑回归中使用聚类测量来研究情境现象

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摘要

STUDY OBJECTIVE: In social epidemiology, it is easy to compute and interpret measures of variation in multilevel linear regression, but technical difficulties exist in the case of logistic regression. The aim of this study was to present measures of variation appropriate for the logistic case in a didactic rather than a mathematical way. Design and PARTICIPANTS: Data were used from the health survey conducted in 2000 in the county of Scania, Sweden, that comprised 10 723 persons aged 18-80 years living in 60 areas. Conducting multilevel logistic regression different techniques were applied to investigate whether the individual propensity to consult private physicians was statistically dependent on the area of residence (that is, intraclass correlation (ICC), median odds ratio (MOR)), the 80% interval odds ratio (IOR-80), and the sorting out index). RESULTS: The MOR provided more interpretable information than the ICC on the relevance of the residential area for understanding the individual propensity of consulting private physicians. The MOR showed that the unexplained heterogeneity between areas was of greater relevance than the individual variables considered in the analysis (age, sex, and education) for understanding the individual propensity of visiting private physicians. Residing in a high education area increased the probability of visiting a private physician. However, the IOR showed that the unexplained variability between areas did not allow to clearly distinguishing low from high propensity areas with the area educational level. The sorting out index was equal to 82%. CONCLUSION: Measures of variation in logistic regression should be promoted in social epidemiological and public health research as efficient means of quantifying the importance of the context of residence for understanding disparities in health and health related behaviour.
机译:研究目的:在社会流行病学中,易于计算和解释多级线性回归中的变化量度,但是在逻辑回归中存在技术困难。这项研究的目的是通过教学而非数学的方式提出适合于逻辑案例的变异度量。设计和参与者:数据来自2000年在瑞典的斯堪尼亚县进行的健康调查,其中包括10 723名18-80岁的人,居住在60个地区。进行多级逻辑回归分析,应用了不同的技术来调查个人咨询私人医生的倾向是否在统计上取决于居住地区(即,组内相关性(ICC),中位数优势比(MOR)),80%区间优势比(IOR-80)和排序索引)。结果:与国际刑事法院相比,MOR提供了更多有关居住区相关性的可解释信息,以了解私人咨询医生的个人倾向。 MOR显示,区域间无法解释的异质性比分析中考虑的个体变量(年龄,性别和教育程度)具有更大的相关性,以了解来访私人医生的个体倾向。居住在高教区增加了看望私人医生的可能性。但是,IOR显示,地区之间无法解释的可变性无法根据地区教育水平清楚地区分低倾向地区和高倾向地区。整理指数等于82%。结论:应在社会流行病学和公共卫生研究中推广对数回归的变化量度,作为量化居住环境对理解健康与健康相关行为差异的重要性的有效手段。

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