Modelo predictivo del consumo de alcohol en los conductores que sufrieron accidentes de tránsito de La Provincia de Trujillo en el mes de agosto del 2017

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The research had as problem: Is the predictive model of logistic regression of alcohol consumption in drivers who suffered traffic accidents in the province of Trujillo, in the month of August of 2017 ?, with the objective of determining, the model predictive of logistic regression of alcohol consum...

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Detalles Bibliográficos
Autor: Nureña Rodríguez, Katherine Lizeth
Formato: tesis de grado
Fecha de Publicación:2017
Institución:Universidad Nacional de Trujillo
Repositorio:UNITRU-Tesis
Lenguaje:español
OAI Identifier:oai:dspace.unitru.edu.pe:20.500.14414/10640
Enlace del recurso:https://hdl.handle.net/20.500.14414/10640
Nivel de acceso:acceso abierto
Materia:Factores de riesgo, Dosaje etílico
Descripción
Sumario:The research had as problem: Is the predictive model of logistic regression of alcohol consumption in drivers who suffered traffic accidents in the province of Trujillo, in the month of August of 2017 ?, with the objective of determining, the model predictive of logistic regression of alcohol consumption in drivers who suffered traffic accidents in the province of Trujillo. Out of a population of 968 drivers in the city of Trujillo, we only worked with a sample of 928 taking into account exclusion criteria. After having performed the corresponding statistical analysis, it was found that the specificity of the model is 64.8%; the model explains between 0.265 and 0.358 of the dependent variable and correctly classifies 86% of the cases, therefore, the model is accepted. The significant variables for the model are: sex, turn of infringement, reason for extraction and shift of extraction, which explain, that the qualitative result. Of which it concludes the risk factors were: sex (masculine), turn of infraction (night), reason for extraction (accident of traffic by shock and traffic accident by outrage) and as protective factor is the shift of extraction (night)
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