Logistic Regression Model of Hazardous Event on Floating Offshore Units

Abstract

Logistic Regression (LR) is used to analyze the relationship between nonmetric dependent variable and metric or dichotomous independent variables. The overall test of relationship among the independent variables and groups defined by the dependent is based on the reduction in the likelihood values for a model which does not contain any independent variables and the model that contains the independent variables. This difference in likelihood follows a chi-square distribution, and is referred to as the model chi-square. The significance test for the final model chi-square (after the independent variables have been added) is our statistical evidence of the presence of a relationship between the dependent variable and the combination of the independent variables. In this study, a hazardous event such as accident has been analyzed using binary logistic regression. The presence of a relationship between the dependent variable and combination of independent variables is based on the statistical significance of the final chi-square model. The result of the best model shows that number of Injuries/Fatalities, number of Chains and operation mode gives the significant contribution in predicting hazardous event on floating offshore units. Keywords: Binary Logistic Regression (BLR); Binary Dependent Variable; Chi-Square Distribution; Floating Units; Oil and Gas. 2010 Mathematics Subject Classification: 62J05