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.
|Advisor:||Usmen, Mumtaz A.|
|Commitee:||Fu, Gongkang, Murat, Alper, Savolainen, Peter|
|School:||Wayne State University|
|School Location:||United States -- Michigan|
|Source:||DAI-B 75/01(E), Dissertation Abstracts International|
|Keywords:||Accident analysis, Construction safety, Crosstabulation, Heavy construction equipment operator, Logistic regression, Predictive model|
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