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http://dx.doi.org/10.5351/KJAS.2020.33.5.555

Comparison of nomograms designed to predict hypertension with a complex sample  

Kim, Min Ho (Department of Statistics, Yeungnam University)
Shin, Min Seok (Department of Statistics, Yeungnam University)
Lee, Jea Young (Department of Statistics, Yeungnam University)
Publication Information
The Korean Journal of Applied Statistics / v.33, no.5, 2020 , pp. 555-567 More about this Journal
Abstract
Hypertension has a steadily increasing incidence rate as well as represents a risk factors for secondary diseases such as cardiovascular disease. Therefore, it is important to predict the incidence rate of the disease. In this study, we constructed nomograms that can predict the incidence rate of hypertension. We use data from the Korean National Health and Nutrition Examination Survey (KNHANES) for 2013-2016. The complex sampling data required the use of a Rao-Scott chi-squared test to identify 10 risk factors for hypertension. Smoking and exercise variables were not statistically significant in the Logistic regression; therefore, eight effects were selected as risk factors for hypertension. Logistic and Bayesian nomograms constructed from the selected risk factors were proposed and compared. The constructed nomograms were then verified using a receiver operating characteristics curve and calibration plot.
Keywords
hypertension; logistic regression; naive Bayesian classifier; nomogram; risk factor;
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Times Cited By KSCI : 4  (Citation Analysis)
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