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Analysis of fatal and nonfatal accidents involving earthmoving equipment operators and on-foot workers.

机译:分析涉及土方设备操作人员和步行工人的致命和非致命事故。

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摘要

In view of the limitations of univariate statistics for studying construction accidents, a multivariate approach was undertaken using crosstabulation analysis and logistic regression.;Heavy construction equipment accidents related data for four type of equipment; backhoe, bulldozer, excavator and scraper were incorporated in the study using categorical variables. Degree of injury indicating the severity of accident outcome (fatal vs. nonfatal) was selected as the dependent variable, and a variety of factors potentially affecting the outcome comprised the independent variables. Cross tabulation results enabled the understanding and evaluation of associations between the research variables, while logistic regression yielded predictive models that helped describe accident severity in terms of the contributing factors. Factors increasing or decreasing the odds of accident severity (degree of injury) in the presence or absence of various factors were identified and quantified. It was concluded that multivariate analysis serves as a much more powerful tool than univariate methods in eliciting information from construction accident data. Union status of workers and the safety training they were provided according to OSHA guidelines vastly affect the degree of injury and lessen the odds of fatality.
机译:鉴于单变量统计研究建筑事故的局限性,采用交叉表分析和逻辑回归的多元方法。使用分类变量将反铲,推土机,挖掘机和铲运机纳入研究。选择表示事故后果严重程度(致命与非致命)的伤害程度作为因变量,各种可能影响结果的因素包括独立变量。交叉制表的结果使人们能够理解和评估研究变量之间的关联,而逻辑回归得出的预测模型有助于根据事故发生的影响因素描述事故的严重程度。在存在或不存在各种因素的情况下,确定和量化增加或降低事故严重性(伤害程度)的几率的因素。结论是,在从施工事故数据中获取信息时,多变量分析比单变量方法功能强大得多。根据OSHA指南提供的工人工会身份和安全培训极大地影响了受伤程度,并降低了死亡几率。

著录项

  • 作者

    Kazan, Esref Emrah.;

  • 作者单位

    Wayne State University.;

  • 授予单位 Wayne State University.;
  • 学科 Engineering Civil.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 175 p.
  • 总页数 175
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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