• The Korean Journal of Applied Statistics
• /
• v.29 no.7
• /
• pp.1311-1327
• /
• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• The Korean Journal of Applied Statistics
• /
• v.33 no.4
• /
• pp.379-393
• /
• 2020

A terminal event such as death may censor an intermediate event such as relapse, but not vice versa in semi-competing risks data, which is often seen in medicine, public health, and epidemiology. We propose a Weibull regression model with a normal frailty to analyze semi-competing risks data when all three transition times of the illness-death model are possibly interval-censored. We construct the conditional likelihood separately depending on the types of subjects: still alive with or without the intermediate event, dead with or without the intermediate event, and dead with the intermediate event missing. Optimal parameter estimates are obtained from the iterative quasi-Newton algorithm after the marginalization of the full likelihood using the adaptive importance sampling. We illustrate the proposed method with extensive simulation studies and PAQUID (Personnes Agées Quid) data.

• The Korean Journal of Applied Statistics
• /
• v.22 no.3
• /
• pp.595-606
• /
• 2009

Two tests were introduced for comparing several survival functions with doubly interval-censored data and illustrated with data surveyed by Korean Cancer Prevention Study (Jee et al., 2005). The test which extended Kim et al. (2006)'s test to the doubly interval-censored data has an advantage over Sun (2006)'s test in terms of saving computation time because the proposed test only depends on the size of risk set, and also the proposed test is applicable to continuous failure time data as well as discrete failure time data unlike Sun's test. Comparing male with female groups on the incubation time of diabetes was highly different and the survival of female group was longer than that of male one. Regardless of gender, the difference in survival functions of four age groups was highly significant with p-value of less than 0.001. This trend was more remarkable for female group than for male one. Simulation results showed that the significance level of both tests was well controlled and the proposed test was better than Sun's test in terms of power.

• The Korean Journal of Applied Statistics
• /
• v.7 no.1
• /
• pp.1-17
• /
• 1994

This article basically considers the calibration problem with censored data from the Bayesian point of view. The Gibbs sampling method is discussed to solve the difficulty encountered in computing the posterior distribution. Also presented is an approach for impementing the Gibbs sampling in actual data situation with the estimation procedures.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2010.05a
• /
• pp.1039-1043
• /
• 2010

본 연구에서는 낙동강, 영산강을 대상으로 과거 사행하도 구간을 직강화함에 따라 절단된 폐천의 형태를 조사하고 이에 대한 유형화를 수행하였다. 폐천 및 구하도 구간을 선정하기 위한 기준은 1918년 근세한국오만분지일지형도를 이용하여 현재의 수치지도와 좌표보정 후 중첩, 비교함으로써 폐천 구간을 파악하였다. 낙동강의 경우 인위적 변형(하도절단형)에 따른 유형분류로 살펴보면, 세부적으로 하도보존형, 타용도전용형, 하도유실형은 각각 9 개소, 2 개소, 3 개소로 조사되었다. 영산강은 세부적으로 하도보존형이 4 개소로 나타났고, 타용도전용형, 하도유실형이 각각 4 개소, 10 개소로 나타났다. 이와 같은 폐천 현황 조사결과는 향후 구하도 복원을 위한 대상지 선정 시 기초자료를 제공하는 기회를 마련할 수 있을 것으로 판단된다.

• The Korean Journal of Applied Statistics
• /
• v.30 no.4
• /
• pp.539-553
• /
• 2017

We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.2
• /
• pp.327-336
• /
• 2014

Recurrent event data occurs when a subject experiences same type of event repeatedly and is found in various areas such as the social sciences, Economics, medicine and public health. To analyze recurrent event data either a total time or a gap time is adopted according to research interest. In this paper, we analyze recurrent event data with incomplete observation gap using a gap time scale. That is, some subjects leave temporarily from a study and return after a while. But it is not available when the observation gaps terminate. We adopt an interval censoring mechanism for estimating the termination time. Furthermore, to model the association among gap times of a subject, a frailty effect is incorporated into a model. Programs included in Survival package of R program are implemented to estimate the covariate effect as well as the variance of frailty effect. YTOP (Young Traffic Offenders Program) data is analyzed with both proportional hazard model and a weibull regression model.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.201-201
• /
• 2011

본 연구는 국내 하천에서 방치되고 있는 구하도 구간의 물리적 상태를 파악함으로써 이를 보전 또는 관리하기위한 기초자료로써 활용하고자 한다. 국내의 구하도 구간은 자연적인 발생보다는 하천의 직강화, 하천부지 이용의 고도화 등 인위적인 교란으로 인해 형성된 것이 대부분이다. 이와 같이 사행구간의 하도가 절단(Cutoff)됨으로써 형성된 구하도는 우각호 형상의 습지형 구하도와 이미 육역화되어 농경지나 나대지로 이용되는 육화형 구하도로 구분할 수 있다. 특히 폐천(Abandoned Channel)화가 진행된 대부분의 습지형 구하도는 수질, 생태계, 육역화, 농업용수 이용 등 다양한 문제점 및 현안을 가지고 있기 때문에 이에 대한 보전 또는 관리가 필요하다. 이를 위해서는 우선적으로 습지형 구하도의 현재를 진단하고 평가하기 위한 연구가 선행되어야 한다. 따라서 본 연구에서는 습지형 구하도를 평가하기 위한 평가지표를 제안하고 이를 만경강 습지형 구하도 5개소에 적용하였다. 평가지표는 국내외에서 제안된 하천환경 평가지표와 RAM(일반기능평가기법)을 토대로 작성하였다. 이 평가지표는 단절된 습지구간에 적정한 지표, 자료 획득의 용이성, 즉시 적용 가능한 것을 우선순위로 선정하였다. 평가지표는 자연도, 서식처, 친수, 수질 등 4개 지표를 세분화한 총 25개 항목으로 제안하였다. 만경강에 대한 물리적 평가결과 습지형 구하도의 경우 서식처, 자연도 부분이 높은 점수를 획득한 반면 수질과 친수 지표는 상대적으로 취약한 것으로 평가 되었다. 이와 같은 결과는 향후 만경강 습지형 구하도에 대한 보전 및 관리계획을 수립함에 있어 주요 고려사항이 될 수 있을 것이다.

• Journal of the Korean Data and Information Science Society
• /
• v.8 no.1
• /
• pp.21-30
• /
• 1997

In accelerated life tests, the failure time of an item is observed under a high stress level, and based on the time the performances of items are investigated at the normal stress level. In this paper, when the mean of the prior of a failure rate is known in the exponential lifetime distribution with censored accelerated failure time data, we utilize the empirical Bayesian method by using the moment estimators in order to estimate the parameters of the prior distribution and obtain the empirical Bayesian predictive density and predictive intervals for a future observation under the normal stress level.

• The Korean Journal of Applied Statistics
• /
• v.33 no.6
• /
• pp.777-789
• /
• 2020

COVID-19 has been rapidly spread world wide since late December 2019. In this paper, our interest is to estimate distribution of incubation time defined as period between infection of virus and the onset. Due to the limit of accessibility and asymptomatic feature of COVID-19 virus, the exact infection and onset time are not always observable. For estimation of incubation time, interval censoring technique is implemented. Furthermore, a competing risk model is applied to estimate the case fatality and cure fraction. Based on the result, the mean incubation time is about 5.4 days and the fatality rate is higher for older and male patient and the cure rate is higher at younger,female and asymptomatic patient.