Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
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Selection of the Best Regression Model to Explain the Variables that Influence Labor Accident Electrical Company Case
Noel Varela Izquierdo, Damaise Perez Fernandez, Omar Bonerge Pineda Lezama and Amelec Viloria
Page: 2956-2962 | Received 21 Sep 2022, Published online: 21 Sep 2022
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Abstract
The present research proposes an alternative to select the best model that explains the relation of the variables that influence the labor accident in an electric power company. Among the techniques and tools used are those of occupational safety and health management, multivariate statistics, generalized linear models, the values of the deviation percentage explained and the adjusted percentage and the Akaike and Bayesian information criteria. The following variables were identified through the mentioned techniques, management commitment, compliance with legislation, prevention planning, training in prevention, updating of occupational risk management and policies that have a significant influence on work accident and through. The percentages and of the previously mentioned criteria were able to show that the logistic regression is the best model that explains the labor accident by presenting the highest percentage and the lowest values of the criteria when compared with the poisson regression and negative binomial models.
How to cite this article:
Noel Varela Izquierdo, Damaise Perez Fernandez, Omar Bonerge Pineda Lezama and Amelec Viloria. Selection of the Best Regression Model to Explain the Variables that
Influence Labor Accident Electrical Company Case.
DOI: https://doi.org/10.36478/jeasci.2017.2956.2962
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2017.2956.2962