合并NVDRS和ACS数据研究自杀的多层次关联。

D. Boulifard, B. Pescosolido
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引用次数: 2

摘要

本文描述了一个新的数据库和相关的自杀事件预测模型,克服了自杀风险因素研究中的长期障碍。该数据库结合了来自国家暴力死亡报告系统(NVDRS)和美国社区调查(ACS)的个人记录,建立了一个病例对照研究样本,其中包括2005-2011年美国16个州的所有已确定的自杀案件,同时忠实地反映了一般人口社会人口统计数据。它支持个人自杀风险的统计模型,该模型包含个人层面的因素,并通过社区比率调节这些因素。该数据库被命名为美国多层次自杀数据集(US-MSDS),在RDC实验室外使用公开可用的ACS微数据开发,并在实验室内使用限制访问的ACS微数据重建。对后一个版本的分析所得到的发现在很大程度上放大了对前一个版本的分析所得到的发现,但也扩展了这些发现。这一经验表明,使用限制访问的ACS数据可以实现的分析精度可以在进行社会研究中发挥重要作用,尽管它也表明,公开可用的ACS数据在进行初步分析和准备使用RDC实验室方面具有相当大的价值。数据库开发策略可能会引起研究其他类型低频率死亡的社会人口风险因素的科学家的兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Examining Multi-Level Correlates of Suicide by Merging NVDRS and ACS Data.
This paper describes a novel database and an associated suicide event prediction model that surmount longstanding barriers in suicide risk factor research. The database comingles person-level records from the National Violent Death Reporting System (NVDRS) and the American Community Survey (ACS) to establish a case-control study sample that includes all identified suicide cases, while faithfully reflecting general population sociodemographics, in sixteen USA states during the years 2005-2011. It supports a statistical model of individual suicide risk that accommodates person-level factors and the moderation of these factors by their community rates. Named the United States Multi-Level Suicide Data Set (US-MSDS), the database was developed outside the RDC laboratory using publicly available ACS microdata, and reconstructed inside the laboratory using restricted access ACS microdata. Analyses of the latter version yielded findings that largely amplified but also extended those obtained from analyses of the former. This experience shows that the analytic precision achievable using restricted access ACS data can play an important role in conducting social research, although it also indicates that publicly available ACS data have considerable value in conducting preliminary analyses and preparing to use an RDC laboratory. The database development strategy may interest scientists investigating sociodemographic risk factors for other types of low-frequency mortality.
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