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http://dx.doi.org/10.5351/KJAS.2018.31.3.329

Comparison of nomogram construction methods using chronic obstructive pulmonary disease  

Seo, Ju-Hyun (Department of Statistics, Yeungnam University)
Lee, Jea-Young (Department of Statistics, Yeungnam University)
Publication Information
The Korean Journal of Applied Statistics / v.31, no.3, 2018 , pp. 329-342 More about this Journal
Abstract
Nomogram is a statistical tool that visualizes the risk factors of the disease and then helps to understand the untrained people. This study used risk factors of chronic obstructive pulmonary disease (COPD) and compared with logistic regression model and naïve Bayesian classifier model. Data were analyzed using the Korean National Health and Nutrition Examination Survey 6th (2013-2015). First, we used 6 risk factors about COPD. We constructed nomogram using logistic regression model and naïve Bayesian classifier model. We also compared the nomograms constructed using the two methods to find out which method is more appropriate. The receiver operating characteristic curve and the calibration plot were used to verify each nomograms.
Keywords
chronic obstructive pulmonary disease (COPD); logistic regression model; naive Bayesian classifier model; nomogram; risk factors;
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