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Article Published In Vol.4 (March-April-2016)

Modeling of Binary Logistic Regression for Obesity among Students in Rural Area of Visakhapatnam

Author : Nagendra Kumar.K,Muniswamy.B D.BVN.Suresh,Sreelatha.Ch and Jeevan Kumar.D

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Logistic regression analysis examines the impact of different factors on dichotomous outcomes by way of estimating the chance of the event occurrence logistic regression, additionally called a logistic model, is a statistical procedure used to model dichotomous effects. In the logistic model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds quantitative relation in logistic regression provides an outline of the probabilistic relationship of the variable and also the outcomes. In conducting logistical regression, choice procedures are utilized in choosing vital predictor variables diagnostics are used to test that assumptions are legitimate which include independent of errors, linearity is the logit for continuous variability absence of multicolinearity, and shortage of strongly influential outliers and take a look at data point is calculated to see the aptnes of the model. This study used the binary logistic regression model to analyze obese (overweight) and obesity among rural area in Visakhapatnam, distance, AP, India. The idea of their demographics profile, records, weight loss program and lifestyle.The results indicate that overweight and obesity of peoples are influenced via obesity in family and also the interaction between a Students quality and routine meals intake.

Keywords: Binary Logistic Regression, logit model, Odds Ratio, Model validation, Hosmer and Lemeshow Test

 

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