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http://dx.doi.org/10.5351/KJAS.2018.31.5.573

Nomogram comparison conducted by logistic regression and naïve Bayesian classifier using type 2 diabetes mellitus (T2D)  

Park, Jae-Cheol (Department of Statistics, Yeungnam University)
Kim, Min-Ho (Department of Statistics, Yeungnam University)
Lee, Jea-Young (Department of Statistics, Yeungnam University)
Publication Information
The Korean Journal of Applied Statistics / v.31, no.5, 2018 , pp. 573-585 More about this Journal
Abstract
In this study, we fit the logistic regression model and naïve Bayesian classifier model using 11 risk factors to predict the incidence rate probability for type 2 diabetes mellitus. We then introduce how to construct a nomogram that can help people visually understand it. We use data from the 2013-2015 Korean National Health and Nutrition Examination Survey (KNHANES). We take 3 interactions in the logistic regression model to improve the quality of the analysis and facilitate the application of the left-aligned method to the Bayesian nomogram. Finally, we compare the two nomograms and examine their utility. Then we verify the nomogram using the ROC curve.
Keywords
logistic regression; naive Bayesian classifier; nomogram; receiver operating characteristic curve(ROC curve); type 2 diabetes mellitus;
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