Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Development of Estimation Algorithm of Latent Ability and Item Parameters in IRT

문항반응이론에서 피험자 능력 및 문항모수 추정 알고리즘 개발

  • Choi, Hang-Seok (Center for Genome Research, Samsung Biomedical Research Institute) ;
  • Cha, Kyung-Joon (Department of Mathematics, Hanyang University) ;
  • Kim, Sung-Hoon (Department of Education, Dongguk University) ;
  • Park, Chung (Department of Early Childhood Education, Pusan National University) ;
  • Park, Young-Sun (Department of Mathematics, Hanyang University)
  • 최항석 (삼성생명과학연구소 유전체연구센터) ;
  • 차경준 (한양대학교 수학과) ;
  • 김성훈 (동국대학교 교육학과) ;
  • 박정 (부산대학교 유아교육학과) ;
  • 박영선 (한양대학교 수학과)
  • Published : 2008.05.30
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Abstract

Item response theory(IRT) estimates latent ability of a subject based on the property of item and item parameters using item characteristics curve(ICC) of each item case. The initial value and another problems occurs when we try to estimate item parameters of IRT(e.g. the maximum likelihood estimate). Thus, we propose the asymptotic approximation method(AAM) to solve the above mentioned problems. We notice that the proposed method can be thought as an alternative to estimate item parameters when we have small size of data or need to estimate items with local fluctuations. We developed 'Any Assess' and tested reliability of the system result by simulating a practical use possibility.

문항반응이론(Item response theory: IRT)에서는 문항이 가지고 있는 특성을 기초로 피험자의 능력을 추정하고 동시에 각 문항별 문항특성곡선(Item characteristics curve: ICC)을 이용하여 문항모수를 추정하게 된다. 그러나 모수추정에 있어서 최대 우도추정의 경우는 초기값과 다른 여러 문제들이 발생할 수 있다. 본 연구에서는 추정 문제 해결방법의 대안으로 점근적 근사화 방법(Asymptotic approximation method: AAM)을 제안한다. 이는 자료의 수가 적거나 국소 변동이 있는 경우에 효과적인 추정방법이라고 할 수 있다. 이에 개발된 'Any Assess' 시스템을 모의실험을 통하여 신뢰성을 검정하였다.

Keywords

References

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