Ridge Regression Analysis in Modeling Body Mass Index (BMI) of Firefighters by Examining the Problem of Multiple Collinearity of Independent Variables (Case Study: Mashhad Fire and Safety Services Organization)
Journal Title: System Engineering and Productivity - Year 2023, Vol 3, Issue 2
Abstract
Body mass index (BMI) is a tool for indicating weight status in adults and is one of the criteria that can be used to express overweight and obesity. In people with a BMI of less than 20 and more than 30 kg/m², the mortality rate increases relatively. The present study aimed to investigate the linear relationship between three independent variables: age, height, and weight, as well as the variable of body mass index of firefighters. This study is based on the objectives and nature of the research, a descriptive field study, based on the data collection method of the survey type, and in terms of the data analysis method, a correlation study type. The statistical population of the study is the firefighters of the Fire and Safety Services Organization of Mashhad Municipality, of which 1600 firefighters were selected as a statistical sample. The necessary data in this study were recorded and collected using annual physical condition assessment tests of firefighters during the years 1399 to 1400 using a specialized body analysis device. SPSS software and Pearson correlation and multivariate regression statistical methods were used to analyze the research data. The results of the research show that there is a strong and direct correlation with a coefficient of 0.99 between the three independent variables of age, height and weight and the dependent variable of body mass index. Using SPSS software and the multiple regression model, a model was obtained to calculate body mass index based on the mentioned independent variables. Finally, ridge regression was used to confirm the obtained model and to investigate the lack of effect of the problem of collinearity of the independent variables. Using ridge regression analysis, it was shown that despite the existence of strong collinearity between the independent variables, this problem of collinearity did not affect the estimation of the coefficients of the multiple regression model and the coefficients of the ridge regression model were obtained very close and equal to the coefficients of the ordinary multiple regression. As a result, the obtained regression model is appropriate, approved and applicable.
Authors and Affiliations
Salmani Bideskan, H. Babaei, P. Gaini, A.
Keywords
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- EP ID EP768185
- DOI 10.22034/msb.2023.709554
- Views 6
- Downloads 0
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