Department of Environmental Health, Boston University School of Public Health, 715 Albany Street, Boston, MA 02118, USA.
Am J Ind Med. 2010 Jan;53(1):37-41. doi: 10.1002/ajim.20787.
Questions 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.
We examined the sensitivity of findings in two studies to alternate sample definitions and study assumptions.
Applying 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%.
Studies 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.
有人对劳工统计局(BLS)和工人赔偿机构发现大量工作场所受伤和患病情况漏报的研究方法提出了质疑。最近对明尼苏达州的一项研究得出结论,BLS 调查捕获了 84-90%的工人赔偿案件。
我们研究了两项研究的结果对不同样本定义和研究假设的敏感性。
假设来源独立,将较早研究中的替代样本构建规则应用于研究中,将 BLS 报告率从 68%提高到 77%。将替代假设应用于最近的明尼苏达州研究,将其对 BLS 报告的高估计值从 90%降低到 53-64%。
将来自不同来源的行政数据进行链接的研究在构建研究数据集和选择分析方法时需要大量的判断。此外,不同的样本构建规则会导致不同的结果。这表明,在无法排除替代方案的情况下,应进行敏感性分析。在这种情况下,敏感性分析支持大量漏报的假设。