• Title/Summary/Keyword: 구간중도절단자료

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Estimation of Survival Function and Median Survival Time in Interval-Censored Data (구간중도절단자료에서 생존함수와 중간생존시간에 대한 추정)

  • Yun, Eun-Young;Kim, Choong-Rak
    • The Korean Journal of Applied Statistics
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    • v.23 no.3
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    • pp.521-531
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    • 2010
  • Interval-censored observations are common in medical and epidemiologic studies; however, limited studies exist due to the complexity and special structure of interval-censoring. This paper introduces the imputation method and the self consistency method in the interval-censored data. We propose a new method of generating random numbers under an interval-censoring set-up. Through simulation studies we compare two methods under various simulation schemes in the sense of the mean squared error for estimating the median survival time and the mean integrated squared error for estimating the survival function. Under a moderate censoring percentage, the mean imputation method showed a better performance than the self-consistency method in estimating the median survival time and the survival function.

Cure Rate Model with Clustered Interval Censored Data (군집화된 구간 중도절단자료에 대한 치유율 모형의 적용)

  • Kim, Yang-Jin
    • The Korean Journal of Applied Statistics
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    • v.27 no.1
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    • pp.21-30
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    • 2014
  • Ordinary survival analysis cannot be applied when a significant fraction of patients may be cured. A cure rate model is the combination of cure fraction and survival model and can be applied to several types of cancer. In this article, the cure rate model is considered in the interval censored data with a cluster effect. A shared frailty model is introduced to characterize the cluster effect and an EM algorithm is used to estimate parameters. A simulation study is done to evaluate the performance of estimates. The proposed approach is applied to the smoking cessation study in which the event of interest is a smoking relapse. Several covariates (including intensive care) are evaluated to be effective for both the occurrence of relapse and the smoke quitting duration.

A two-sample test with interval censored competing risk data using multiple imputation (다중대체방법을 이용한 구간 중도 경쟁 위험 모형에서의 이표본 검정)

  • Kim, Yuwon;Kim, Yang-Jin
    • The Korean Journal of Applied Statistics
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    • v.30 no.2
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    • pp.233-241
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    • 2017
  • Interval censored data frequently occur in observation studies where the subject is followed periodically. In this paper, our interest is to suggest a test statistic to compare the CIF of two groups with interval censored failure time data in the presence of competing risks. Gray (1988) suggested a test statistic for right censored data that motivated a well-known Fine and Gray's subdistribution hazard model. A multiple imputation technique is adopted to adopt Gray's test statistic to interval censored data. The powers and sizes of the suggested method are investigated through diverse simulation schemes. The main merit of the suggested method is its simplicity to implement with existing software for right censored data. The method is illustrated by analyzing Bangkok's HIV cohort dataset.

A concordance test for bivariate interval censored data using a leverage bootstrap (지렛대 붓스트랩을 이용한 이변량 구간 중도 절단 자료의 일치성 검정)

  • Kim, Yang-Jin
    • The Korean Journal of Applied Statistics
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    • v.32 no.5
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    • pp.753-761
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    • 2019
  • A test procedure based on a Kendall's τ statistic is proposed for the association of bivariate interval censored data. In particular, a leverage bootstrap technique is applied to replace unknown failure times and a classical adjustment method is applied for treating tied observations. The suggested method shows desirable results in simulation studies. An AIDS dataset is analyzed with the suggested method.

Modeling Clustered Interval-Censored Failure Time Data with Informative Cluster Size (군집의 크기가 생존시간에 영향을 미치는 군집 구간중도절단된 자료에 대한 준모수적 모형)

  • Kim, Jinheum;Kim, Youn Nam
    • The Korean Journal of Applied Statistics
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    • v.27 no.2
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    • pp.331-343
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    • 2014
  • We propose two estimating procedures to analyze clustered interval-censored data with an informative cluster size based on a marginal model and investigate their asymptotic properties. One is an extension of Cong et al. (2007) to interval-censored data and the other uses the within-cluster resampling method proposed by Hoffman et al. (2001). Simulation results imply that the proposed estimators have a better performance in terms of bias and coverage rate of true value than an estimator with no adjustment of informative cluster size when the cluster size is related with survival time. Finally, they are applied to lymphatic filariasis data adopted from Williamson et al. (2008).

Statistical Analysis of Clustered Interval-Censored Data with Informative Cluster Size (정보적군집 크기를 가진 군집화된 구간 중도절단자료 분석을 위한결합모형의 적용)

  • Kim, Yang-Jin;Yoo, Han-Na
    • Communications for Statistical Applications and Methods
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    • v.17 no.5
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    • pp.689-696
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    • 2010
  • Interval-censored data are commonly found in studies of diseases that progress without symptoms, which require clinical evaluation for detection. Several techniques have been suggested with independent assumption. However, the assumption will not be valid if observations come from clusters. Furthermore, when the cluster size relates to response variables, commonly used methods can bring biased results. For example, in a study on lymphatic filariasis, a parasitic disease where worms make several nests in the infected person's lymphatic vessels and reside until adulthood, the response variable of interest is the nest-extinction times. Since the extinction times of nests are checked by repeated ultrasound examinations, exact extinction times are not observed. Instead, data are composed of two examination points: the last examination time with living worms and the first examination time with dead worms. Furthermore, as Williamson et al. (2008) pointed out, larger nests show a tendency for low clearance rates. This association has been denoted as an informative cluster size. To analyze the relationship between the numbers of nests and interval-censored nest-extinction times, this study proposes a joint model for the relationship between cluster size and clustered interval-censored failure data.

Comparing Survival Functions with Doubly Interval-Censored Data: An Application to Diabetes Surveyed by Korean Cancer Prevention Study (이중구간중도절단된 생존자료의 생존함수 비교를 위한 검정: 한국인 암 예방연구 중 당뇨병에의 응용)

  • Jee, Sun-Ha;Nam, Chung-Mo;Kim, Jin-Heum
    • The Korean Journal of Applied Statistics
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    • v.22 no.3
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    • pp.595-606
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    • 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.