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Rank Tracking Probabilities using Linear Mixed Effect Models

선형 혼합 효과 모형을 이용한 순위 추적 확률

  • Received : 2015.03.16
  • Accepted : 2015.04.06
  • Published : 2015.04.30

Abstract

An important scientific objective of longitudinal studies involves tracking the probability of a subject having certain health condition over the course of the study. Proper definitions and estimates of disease risk tracking have important implications in the design and analysis of long-term biomedical studies and in developing guidelines for disease prevention and intervention. We study in this paper a class of rank-tracking probabilities to describe a subject's conditional probabilities of having certain health outcomes at two different time points. Linear mixed effects models are considered to estimate the tracking probabilities and their ratios of interest. We apply our methods to an epidemiological study of childhood cardiovascular risk factors.

경시적 자료 연구의 중요한 주제 중의 하나는 시간이 지남에 따라 개인의 건강 상태가 어떻게 변하는지를 추적하는 확률이다. 질병의 상태를 시간의 흐름에 따라 추적하는 것은 장기간에 걸친 임상적 관찰 연구의 계획과 분석, 그리고 질병의 예방과 치료에 중요한 의미를 지닌다. 본 논문에서는 두 다른 시점에서 각 개인의 건강 상태에 대한 조건부 확률을 추정해내는 순위 추적 확률에 대하여 연구하였다. 순위 추적 확률과 순위 추적 확률비를 추정하기 위하여 선형 혼합 효과 모형을 고려하였다. 본 논문의 방법은 아동을 대상으로 심혈관계 질환의 위험요인을 연구하는 역학 자료에 적용되었다.

Keywords

References

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