• 응용통계연구
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• 제21권6호
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• pp.933-945
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• 2008

발병연령과 이에 관련되었다고 의심되는 좌위와의 연관성이 실제로 존재하는 경우에 유전자형 정보에 따라 발병연령(age of onset) 분포의 추세가 뚜렷하게 나타난다. 그러나 연관성 검정에서 주로 채택하고 있는 발병연령의 상한연령(cutoff age)을 제한하는 표본추출은 유전자형에 따른 여러 군의 미완결 자료의 분포가 다름을 초래하게 되며, 이러한 미완결 분포 차이는 발병연령의 추세 검정에 있어 효율성을 낮추는 원인이 된다. 일반적으로 두 군의 경우에 그 대책으로써 윌콕슨(Wilcoxon) 통계량보다는 미완결 자료의 분포가 다름에 영향을 덜 받는다고 알려진 로그순위(log-rank) 통계량을 사용한다. 본 논문에서는 로그순위 통계량 적용을 유전자형에 따른 여러 군의 경우로 확장하여 Jones와 Browley (1989)에 언급된 일반화 로그순위 추세 검정통계량(generalized log-rank statistic for trend)을 제안하며, 연관성 연구에서 이 검정통계량과 여러 다른 추세 검정통계량의 효율성을 모의실험으로 알아본다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.357-360
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• 2005

In this paper we consider the well-known semiparametric proportional hazards (PH) models for survival analysis. These models are usually used with few covariates and many observations (subjects). But, for a typical setting of gene expression data from DNA microarray, we need to consider the case where the number of covariates p exceeds the number of samples n. For a given vector of response values which are times to event (death or censored times) and p gene expressions (covariates), we address the issue of how to reduce the dimension by selecting the significant genes. This approach enable us to estimate the survival curve when n < < p. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. The approach creates additional flexibility by allowing the imposition of constraints, such as bounding the dimension via a prior, which in effect works as a penalty. To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method. We demonstrate the use of the methodology to diffuse large B-cell lymphoma (DLBCL) complementary DNA(cDNA) data.

• International Journal of Reliability and Applications
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• 제16권2호
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• pp.55-79
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• 2015

It is well known that using any additional information in the estimation of unknown parameters with new sample of observations diminishes the sampling units needed and minimizes the risk of new estimators. There are many rational reasons to assure that the existence of additional information in practice and there exists many practical cases in which additional information is available in the form of target value (initial value) about the unknown parameters. This article is described the problem of how the prior initial value about the unknown parameters can be utilized and combined with classical Bayes estimator to get a new combination of Bayes estimator and prior value to improve the properties of the new combination. In this article, two classes of Bayes-shrinkage and preliminary test Bayes-shrinkage estimators are proposed for the scale parameter of exponential distribution. The bias, risk and risk ratio expressions are derived and studied. The performance of the proposed classes of estimators is studied for different choices of constants engaged in the estimators. The comparisons, conclusions and recommendations are demonstrated.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.127-135
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• 2001

In this paper, we consider a simple method for testing the assumption of independent censoring on the basis of a Cox proportional hazards regression model with a time-dependent covariate. This method involves a two-stage sampling in which a random subset of censored observations is selected and followed-up until their true survival times are observed. Lee and Wolfe(1998) proposed an adjusted estimate of the survivor function for the dependent censoring under a proportional hazards alternative. This paper extends their result to obtain a bootstrap confidence interval for the adjusted survivor function under the dependent censoring. The proposed procedure is illustrated with an example of a clinical trial for lung cancer analysed in Lee and Wolfe(1998).

• International Journal of Reliability and Applications
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• 제2권1호
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• pp.1-26
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• 2001

The purpose of this paper is to introduce a proportional reversed hazard rate model, in contrast to the celebrated proportional hazard model, and study some of its structural properties. Some criteria of ageing are presented and the inheritance of the ageing notions (of the base line distribution) by the proposed model are studied. Two important data sets are analyzed: one uncensored and the other having some censored observations. In both cases, the confidence bands for the failure rate and survival function are investigated. In one case the failure rate is bathtub shaped and in the other it is upside bath tub shaped and thus the failure rates are non-monotonic even though the baseline failure rate is monotonic. In addition, the estimates of the turning points of the failure rates are provided.

• Communications for Statistical Applications and Methods
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• 제29권6호
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• pp.665-677
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• 2022

This paper proposes a new estimation method based on the maximum product of spacings for estimating unknown parameters of the three-parameter Weibull distribution under a generalized Type-II progressive hybrid censoring scheme which guarantees a constant number of observations and an appropriate experiment duration. The proposed approach is appropriate for a situation where the maximum likelihood estimation is invalid, especially, when the shape parameter is less than unity. Furthermore, it presents the enhanced performance in terms of the bias through the Monte Carlo simulation. In particular, the superiority of this approach is revealed even under the condition where the maximum likelihood estimation satisfies the classical asymptotic properties. Finally, to illustrate the practical application of the proposed approach, the real data analysis is conducted, and the superiority of the proposed method is demonstrated through a simple goodness-of-fit test.

• 응용통계연구
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• 제8권2호
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• pp.109-119
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• 1995

두 모집단에서 임의로 관측중단도니 두 표본을 얻었을 때, 두 모집단의 분포가 같다는 가설을 검정하기 위한 카이제곱 검정방법이 제안되었다. 여기서 제안된 통계량은 대립가설이 두 모집단의 분포가 같지 않다는 양측가설일 때 쓰일 수 있다. 귀무가설이 사실일 때 제안된 통계량의 극한분포는 카이제곱 분포가 된다. 두 가지 형태의 카이제곱 검정통계량이 제안되었는데, 하나는 product-limit 추정치로부터 얻은 관측된 칸(cell) 확률의 차이들의 벡터의 이차형식으로 표현된 것이고, 다른 하나는 간단한 합의 모양으로 표현된 것이다. 두 형태의 검정통계량을 사용하여 암치료를 위한 화학요법 실험으로부터 얻은 자료를 분석하여 보았다.

• 응용통계연구
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• 제23권4호
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• pp.705-713
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• 2010

마이크로어레이 실험 결과로부터 생존예측지표를 개발하는 일은 관찰 유전자수가 환자의 수보다 훨씬 많고 또 반응변수가 중도절단이 포함된 생존시간이기 때문에 어려운 작업이다. 또한 개별유전자 분석의 문제점이 대두되면서 동일한 대사기능을 수행하는 유전자들의 집합을 대상으로 분석하는 방법이 대두되고 있다. DLBCL 환자들의 마이크로어레이 유전자 발현 자료와 생존시간, 유전자들의 대사경로 정보를 바탕으로 생물학적 해석이 쉬운 생존예측지표를 찾고 그 정확성을 검정하는 pilot study를 실시하였다. 또한 유전자 걸러내기가 지표의 효율성에 미치는 영향력도 비교하여 보았다.

• 응용통계연구
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• 제25권4호
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• pp.621-632
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• 2012

Recurrent event data can be easily found in longitudinal studies such as clinical trials, reliability fields, and the social sciences; however, there are a few observations that disappear temporarily in sight during the follow-up and then suddenly reappear without notice like the Young Traffic Offenders Program(YTOP) data collected by Farmer et al. (2000). In this article we focused on inference for a cumulative mean function of the recurrent event data with these incomplete observation gaps. Defining a corresponding risk set would be easily accomplished if we know the exact intervals where the observation gaps occur. However, when they are incomplete (if their starting times are known but their terminating times are unknown) we need to estimate a distribution function for the terminating times of the observation gaps. To accomplish this, we treated them as interval-censored and then estimated their distribution using the EM algorithm proposed by Turnbull (1976). We proposed a nonparametric estimator for the cumulative mean function and also a nonparametric test to compare the cumulative mean functions of two groups. Through simulation we investigated the finite-sample performance of the proposed estimator and proposed test. Finally, we applied the proposed methods to YTOP data.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 춘계 학술발표회 논문집
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• pp.17-23
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• 2005

In this paper we consider the well-known semiparametric proportional hazards models for survival analysis. These models are usually used with few covariates and many observations (subjects). But, for a typical setting of gene expression data from DNA microarray, we need to consider the case where the number of covariates p exceeds the number of samples n. For a given vector of response values which are times to event (death or censored times) and p gene expressions(covariates), we address the issue of how to reduce the dimension by selecting the significant genes. This approach enables us to estimate the survival curve when n ${\ll}$p. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. The approach creates additional flexibility by allowing the imposition of constraints, such as bounding the dimension via a prior, which in effect works as a penalty To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method. We demonstrate the use of the methodology to diffuse large B-cell lymphoma (DLBCL) complementary DNA (cDNA) data and Breast Carcinomas data.