Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Review and discussion of marginalized random effects models

주변화 변량효과모형의 조사 및 고찰

  • Received : 2014.07.29
  • Accepted : 2014.09.24
  • Published : 2014.11.30
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Abstract

Longitudinal categorical data commonly occur from medical, health, and social sciences. In these data, the correlation of repeated outcomes is taken into account to explain the effects of covariates exactly. In this paper, we introduce marginalized random effects models that are used for the estimation of the population-averaged effects of covariates. We also review how these models have been developed. Real data analysis is presented using the marginalized random effects.

경시적 범주형자료 (longitudinal categorical data)는 의학, 보건학, 그리고 사회과학에서 많이 발생하는 자료이다. 이러한 자료는 반복측정으로 인한 결과치들의 상관관계를 설명하면서 공변량의 효과를 설명해야 한다. 이 논문에서 모집단에 대한 공변량의 효과를 추정하면서 우도함수에 기초한 모형인 주변화 변량효과모형 (marginalized random effects model)을 소개하고, 그 모형의 어떻게 발전했는지를 고찰한다. 그리고 실제 자료를 이용하여 제시된 모형을 설명한다.

Keywords

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