Division of Epidemiology, Berkeley School of Public Health, University of California, Berkeley, CA, USA.
J Epidemiol Community Health. 2013 Feb;67(2):159-65. doi: 10.1136/jech-2012-201317. Epub 2012 Aug 22.
In multilevel studies, strong correlations of neighbourhood exposures with individual and neighbourhood confounders may generate problems with non-positivity (ie, inferences that are 'off-support'). The authors used propensity restriction and matching to (1) assess the utility of propensity restriction to ensure analyses are 'on-support' and (2) examine the relation between collective efficacy and violence in a previously unstudied city.
Associations between neighbourhood collective efficacy and violent victimisation were estimated in data from New York City in 2005 (n=4000) using marginal models and propensity matching.
In marginal models adjusted for individual confounders and limited to observations 'on-support', under conditions of high collective efficacy, the estimated prevalence of violent victimisation was 3.5/100, while under conditions of low collective efficacy, it was 7.5/100, resulting in a difference of 4.0/100 (95% CI 2.6 to 5.8). In propensity-matched analysis, the comparable difference was 4.0/100 (95% CI 2.1 to 5.9). In analyses adjusted for individual and neighbourhood confounders and limited to observations 'on-support', the difference in violent victimisation associated with collective efficacy was 3.1/100 (95% CI 1.2 to 5.2) in marginal models and 2.4/100 (95% CI 0.2 to 4.5) in propensity-matched analysis. Analyses without support restrictions produced surprisingly similar results.
Under conditions of high collective efficacy, there was about half the prevalence of violence compared with low collective efficacy. The results contribute to a growing body of evidence that suggests collective efficacy may shape violence, and illustrate how careful techniques can be used to disentangle exposures from highly correlated confounders without relying on model extrapolation.
在多层次研究中,邻里暴露与个体和邻里混杂因素的强相关性可能会导致非正定性问题(即,推断“偏离支持”)。作者使用倾向限制和匹配来:(1)评估倾向限制的效用,以确保分析是“支持”的;(2)在一个以前未研究过的城市中检验集体效能与暴力之间的关系。
使用边缘模型和倾向匹配,在 2005 年纽约市的数据中估计邻里集体效能与暴力受害之间的关联(n=4000)。
在调整了个体混杂因素且仅限于“支持”观察的边缘模型中,在高集体效能条件下,暴力受害的估计患病率为 3.5/100,而在低集体效能条件下,为 7.5/100,差异为 4.0/100(95%CI 2.6 至 5.8)。在倾向匹配分析中,可比差异为 4.0/100(95%CI 2.1 至 5.9)。在调整了个体和邻里混杂因素且仅限于“支持”观察的分析中,与集体效能相关的暴力受害差异在边缘模型中为 3.1/100(95%CI 1.2 至 5.2),在倾向匹配分析中为 2.4/100(95%CI 0.2 至 4.5)。没有支持限制的分析产生了惊人相似的结果。
在高集体效能条件下,与低集体效能相比,暴力的患病率约为一半。结果为越来越多的证据表明集体效能可能影响暴力提供了贡献,并说明了如何在不依赖模型外推的情况下,使用谨慎的技术来将暴露与高度相关的混杂因素区分开来。