Joint model of longitudinal data with informative observation time and competing risk

결시적 자료에서 관측 중단을 모형화하기 위해 사용되는 경쟁 위험의 적용과 결합 모형

Kim, Yang-Jin

  • Received : 2015.12.14
  • Accepted : 2016.01.15
  • Published : 2016.02.29


Longitudinal data often occur in prospective follow-up studies. Joint model for longitudinal data and failure time has been applied on several works. In this paper, we extend it to the case where longitudinal data involve informative observation time process as well as competing risks survival times. We use a likelihood approach and derive an EM algorithm to obtain maximum likelihood estimate of parameters. A suggested joint model allows us to make inferences for three components: longitudinal outcome, observation time process and competing risk failure time. In addition, we can test the association among these components. In this paper, liver cirrhosis patients' data is analyzed. The relationship between prothrombin times measured at irregular visiting times and drop outs is investigated with a joint model.


competing risk;Drop out;informative observation process;joint model;longitudinal data;random effect


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Supported by : 숙명여자대학교