Researcher judgment and study design: challenges of using administrative data.
Researcher judgment and study design: challenges of using administrative data.
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研究人员的判断和研究设计：使用管理数据的挑战。
DOI：
10.1002/ajim.20787
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发表时间：
2010
影响因子：
3.5
通讯作者：
Ozonoff,Al
中科院分区：
文献类型：
--
作者：
Boden,LeslieI;Ozonoff,Al
背景问题已经提出了有关的研究方法，发现大量低估的工伤和疾病的劳工统计局（BLS）和工人的赔偿机构。最近的一项研究明尼苏达州的结论是，劳工统计局的调查捕获84-90%的工人的补偿cases.MethodsWe研究结果的敏感性，在两项研究中，以替代样本的定义和研究assumptions.ResultsApplying替代样本的建设规则，以较早的研究增加估计劳工统计局的报告率从68%到77%，假设源独立。将替代假设应用到最近的明尼苏达州研究中，将其对BLS报告的高估计从90%降低到53-64%.ConclusionsStudies链接来自不同来源的行政数据需要在构建研究数据集和选择分析方法方面做出实质性判断。此外，不同的样本构造规则导致不同的结果。这表明，当不能排除替代方案时，应进行敏感性分析。在这种情况下，敏感性分析支持重大漏报的假设。Am. J. Ind. Med. 53：37-41，2010.© 2009 Wiley利斯公司
BackgroundQuestions have been raised about methods of studies finding substantial undercounting of workplace injuries and illnesses by the Bureau of Labor Statistics (BLS) and workers' compensation agencies. A more recent study of Minnesota concluded that the BLS survey captures 84–90% of workers' compensation cases.MethodsWe examined the sensitivity of findings in two studies to alternate sample definitions and study assumptions.ResultsApplying alternate sample construction rules to the earlier study increased estimated BLS reporting rates from 68% to 77%, assuming source independence. Applying alternate assumptions to the more recent Minnesota study reduced its high estimate of BLS reporting from 90% to 53–64%.ConclusionsStudies linking administrative data from different sources require substantial judgment in constructing research datasets and choosing analytic methods. Moreover, different sample construction rules lead to different results. This suggests that sensitivity analysis should be carried out when alternatives cannot be ruled out. In this case, sensitivity analysis supports the hypothesis of substantial underreporting. Am. J. Ind. Med. 53:37–41, 2010. © 2009 Wiley‐Liss, Inc.