Look-alike modelling in violence-related research: a missing data approach

Estela Barbosa, Niels Blom, Annie Bunce
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Abstract

Violence as a phenomena has been analysed in silo due to difficulties in accessing data and concerns for the safety of those exposed. While there is some literature on violence and its associations using individual datasets, analyses using combined sources of data are very limited. Ideally data from the same individuals would enable linkage and a longitudinal understanding of experiences of violence and their (health) impacts and consequences. However, in the absence of directly linked data, look-alike modelling may provide an innovative and cost-effective approach to exploring patterns and associations in violence-related research in a multi-sectorial setting. We approached the problem of data integration as a missing data problem to create a synthetic combined dataset. We combined data from the Crime Survey of England and Wales with administrative data from Rape Crisis, focussing on victim-survivors of sexual violence in adulthood. Multiple imputation with chained equations were employed to collate/impute data from different sources. To test whether this procedure was effective, we compared regressions analyses for the individual and combined synthetic datasets on a binary, continuous and categorical variables. Our results show that the effect sizes for the combined dataset reflect those from the dataset used for imputation. The variance is higher, resulting in fewer statistically significant estimates. We extended our testing to an outcome measures and finally applied the technique to a variable fully missing in one data source. Our approach reinforces the possibility to combine administrative with survey datasets using look-alike methods to overcome existing barriers to data linkage.
暴力相关研究中的相似模型:一种缺失数据方法
由于难以获得数据和担心受影响者的安全,一直以来都是孤立地分析暴力现象。虽然有一些文献利用单个数据集对暴力及其关联进行了研究,但利用综合数据来源进行的分析却非常有限。理想情况下,来自同一人的数据可以进行关联,并对暴力经历及其(健康)影响和后果进行纵向了解。然而,在缺乏直接关联数据的情况下,"外观相似 "建模可能会提供一种创新且具有成本效益的方法,用于在多部门环境中探索暴力相关研究的模式和关联。我们将英格兰和威尔士犯罪调查的数据与强奸危机组织的行政数据相结合,重点关注成年期性暴力的受害者和幸存者。我们采用了链式方程多重估算法来整理/估算不同来源的数据。为了检验这一程序是否有效,我们比较了对二元变量、连续变量和分类变量的单个数据集和合并合成数据集的回归分析。结果显示,合并数据集的效应大小反映了用于估算的数据集的效应大小。方差较大,导致具有统计意义的估计值较少。我们将测试扩展到结果测量,最后将该技术应用于一个数据源中完全缺失的变量。我们的方法加强了使用外观相似方法将行政数据集与调查数据集结合起来的可能性,从而克服了现有的数据关联障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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