The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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A Study of Effect on the Smoking Status using Multilevel Logistic Model

다수준 로지스틱 모형을 이용한 흡연 여부에 미치는 영향 분석

  • Lee, Ji Hye (Department of Information and Statistics, Chungbuk National University) ;
  • Heo, Tae-Young (Department of Information and Statistics, Chungbuk National University)
  • 이지혜 (충북대학교 정보통계학과) ;
  • 허태영 (충북대학교 정보통계학과)
  • Received : 2013.11.15
  • Accepted : 2014.01.06
  • Published : 2014.02.28
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Abstract

In this study, we analyze the effect on the smoking status in the Seoul Metropolitan area using a multilevel logistic model with Community Health Survey data from the Korea Centers for Disease Control and Prevention. Intraclass correlation coefficient (ICC), profiling analysis and two types of predicted value were used to determine the appropriate multilevel analysis level. Sensitivity, specificity, percentage of correctly classified observations (PCC) and ROC curve evaluated model performance. We showed the applicability for multilevel analysis allowed for the possibility that different factors contribute to within group and between group variability using survey data.

본 연구에서는 질병관리본부에서 매년 조사하고 있는 지역사회 건강조사 자료를 이용하여 서울시 지역을 대상으로 개인의 흡연 여부에 대한 영향 요인을 확인하고 지역간 차이를 모형에 반영시키는 다수준 로지스틱 모형을 이용하여 분석하였다. 다수준 모형에서의 적합한 분석 모형의 수준을 결정하기 위해 ICC(intraclass correlation coefficient)와 프로파일링 분석, 수준별 모형의 예측정확도를 이용하였다. 제안된 모형들의 성능을 평가하기 위해 민감도, 특이도, 정확도를 구하고 ROC curve를 작성하였다. 결과적으로 지역사회 건강조사 자료와 같이 개인과 집단 변수를 동시에 고려할 수 있다면 다양한 다수준 모형의 적용이 가능하며 활용성이 높다는 것을 알 수 있었다.

Keywords

References

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