응용통계연구 (The Korean Journal of Applied Statistics)

  • 제34권2호
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  • Pages.141-152
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  • 2021
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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AUC 차이를 이용한 미결정자 추론방법

Undecided inference using the difference of AUCs

  • 홍종선 (성균관대학교 통계학과) ;
  • 나해린 (성균관대학교 통계학과)
  • Hong, Chong Sun (Department of Statistics, Sungkyunkwan University) ;
  • Na, Hae Rin (Department of Statistics, Sungkyunkwan University)
  • 투고 : 2020.11.09
  • 심사 : 2021.01.05
  • 발행 : 2021.04.30
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초록

미결정자 추론을 재평가하기 위해 기존 변수에 새로운 변수들을 추가하는 통계 모형이 필요하다. 미결정자와 결정자의 양성률은 다르게 계산되기 때문에 MNAR 가정이 필요하다. 본 연구에서는 두 통계적 모형이 계층 관계를 가지고 있으므로, 두 AUC 차이의 신뢰구간을 이용하여 MNAR 가정하에서 미결정자를 추론한다. AUC 차이 신뢰구간의 추정방법 중에서 모의실험을 통하여 네 종류의 방법의 성능이 우수함을 발견하였다. 그리고 네 종류의 방법을 바탕으로 로지스틱 회귀를 이용한 미결정자 추론에 도움이 되는 변수를 선택하는 방법을 제안한다.

A new statistical model needs additional variables in order to re-evaluate the undecided inference. Then the MNAR assumption is required, since the probabilities for the positivity of the indeterminant and the determinant is calculated differently. In this study, since two statistical models have a hierarchical relationship, we determine the undecided inference under the MNAR assumption using the confidence interval of the difference between two AUCs. Among many methods of estimating the confidence interval of the AUC difference, it is found that four kinds of methods show excellent performance through simulations. And based on these methods, we propose a variable selection method that are useful for the undecided inference using logistic regression models.

키워드

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