• Journal of the Korean Data and Information Science Society
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• 제9권1호
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• pp.37-45
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• 1998

임의중도절단된 생존시간자료에서 생존함수에 대한 동시신뢰대를 근사식이나 표없이 구성하는 간단한 방법을 제안하였다. 그리고 모의실험을 통하여 기존의 동시신뢰대와 포함확률측면에서 서로 비교하고, 실제자료에 적용하여 보았다.

• Journal of the Korean Data and Information Science Society
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• 제8권2호
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• pp.225-230
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• 1997

We, in this paper, propose an estimator of mean residual life function by using the residual survival function under random censoring and prove the uniform consistency and weak convergence result of this estimator. Also an example is illustrated by the real data.

• Journal of the Korean Data and Information Science Society
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• 제15권3호
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• pp.605-616
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• 2004

In this paper we consider the proportional hazard models for survival analysis in the microarray data. For a given vector of response values and gene expressions (covariates), we address the issue of how to reduce the dimension by selecting the significant genes. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method.

• Asian Pacific Journal of Cancer Prevention
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• 제15권19호
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• pp.8371-8376
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• 2014

Background: The use of statistical methods has become an imperative tool in breast cancer survival data analysis. The purpose of this study was to develop the best statistical probability model using the Bayesian method to predict future survival times for the black non-Hispanic female breast cancer patients diagnosed during 1973-2009 in the U.S. Materials and Methods: We used a stratified random sample of black non-Hispanic female breast cancer patient data from the Surveillance Epidemiology and End Results (SEER) database. Survival analysis was performed using Kaplan-Meier and Cox proportional regression methods. Four advanced types of statistical models, Exponentiated Exponential (EE), Beta Generalized Exponential (BGE), Exponentiated Weibull (EW), and Beta Inverse Weibull (BIW) were utilized for data analysis. The statistical model building criteria, Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were used to measure the goodness of fit tests. Furthermore, we used the Bayesian approach to obtain the predictive survival inferences from the best-fit data based on the exponentiated Weibull model. Results: We identified the highest number of black non-Hispanic female breast cancer patients in Michigan and the lowest in Hawaii. The mean (SD), of age at diagnosis (years) was 58.3 (14.43). The mean (SD), of survival time (months) for black non-Hispanic females was 66.8 (30.20). Non-Hispanic blacks had a significantly increased risk of death compared to Black Hispanics (Hazard ratio: 1.96, 95%CI: 1.51-2.54). Compared to other statistical probability models, we found that the exponentiated Weibull model better fits for the survival times. By making use of the Bayesian method predictive inferences for future survival times were obtained. Conclusions: These findings will be of great significance in determining appropriate treatment plans and health-care cost allocation. Furthermore, the same approach should contribute to build future predictive models for any health related diseases.

• Asian Pacific Journal of Cancer Prevention
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• 제14권2호
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• pp.825-828
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• 2013

Objective: The objective of this study was to determine the five-year survival among patients with cervical cancer treated in Hospital Universiti Sains Malaysia. Methods: One hundred and twenty cervical cancer patients diagnosed between $1^{st}$ July 1995 and $30^{th}$ June 2007 were identified. Data were obtained from medical records. The survival probability was determined using the Kaplan-Meier method and the log-rank test was applied to compare the survival distribution between groups. Results: The overall five-year survival was 39.7% [95%CI (Confidence Interval): 30.7, 51.3] with a median survival time of 40.8 (95%CI: 34.0, 62.0) months. The log-rank test showed that there were survival differences between the groups for the following variables: stage at diagnosis (p=0.005); and primary treatment (p=0.0242). Patients who were diagnosed at the latest stage (III-IV) were found to have the lowest survival, 18.4% (95%CI: 6.75, 50.1), compared to stage I and II where the five-year survival was 54.7% (95%CI: 38.7, 77.2) and 40.8% (95%CI: 27.7, 60.3), respectively. The five-year survival was higher in patients who received surgery [52.6% (95%CI: 37.5, 73.6)] as a primary treatment compared to the non-surgical group [33.3% (95%CI: 22.9, 48.4)]. Conclusion: The five-year survival of cervical cancer patients in this study was low. The survival of those diagnosed at an advanced stage was low compared to early stages. In addition, those who underwent surgery had higher survival than those who had no surgery for primary treatment.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.927-939
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• 2020

This study aims at investigating the effects of internal control effectiveness on business survival of food businesses in Thailand through the mediators of productivity improvement and value creation. In this study, 155 food businesses in Thailand are the samples of the study. The results show that internal control effectiveness has a significant influence on productivity improvement and business survival. Productivity improvement critically affects value creation and business survival while value creation is an important determinant of business survival. However, internal control effectiveness has no relationship with value creation. Also, productivity improvement explicitly mediates the internal control effectiveness-business survival relationships. In summary, internal control effectiveness can enhance firms' sustainable competitive advantage, superior performance and long-term survival. Firms need to focus on internal control effectiveness through investing their assets and resources and utilizing their abilities, competencies and capabilities in order to continuously develop and improve their appropriate concepts and characteristics in an organization. Better internal control effectiveness definitely leads to more long-term survival. To generalize the research results, future research needs to collect data from other businesses and industries. Increased response rate of the study is important for future research to verify and confirm the research results.

• Journal of Korean Neurosurgical Society
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• 제53권4호
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• pp.228-234
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• 2013

Objective : We have limited understanding on the presentation and survival of primary spinal sarcomas. The survival, recurrence rate, and related prognostic factors were investigated after treatment for primary sarcomas of the spine. Methods : Retrospective analysis of medical records and radiological data was done for 29 patients in whom treatment was performed due to primary sarcoma of the spine from 2000 to 2010. As for treatment method, non-radical operation, radiation therapy, and chemotherapy were simultaneously or sequentially combined. Overall survival (OS), progression free survival (PFS), ambulatory function, and pain status were analyzed. In addition, factors affecting survival and recurrence were analyzed : age (${\leq}42$ or ${\geq}43$), gender, tumor histologic type, lesion location (mobile spine or rigid spine), weakness at diagnosis, pain at diagnosis, ambulation at diagnosis, initial treatment, radiation therapy, kind of irradiation, surgery, chemotherapy and distant metastasis. Results : Median OS was 60 months, the recurrence rate was 79.3% and median PFS was 26 months. Patients with distant metastasis showed significantly shorter survival than those without metastasis. No factors were found to be significant relating to recurrence. Prognostic factor associated with walking ability was the presence of weakness at diagnosis. Conclusion : Primary spinal sarcomas are difficult to cure and show high recurrence rate. However, the development of new treatment methods is improving survival.

• 국토계획
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• 제54권5호
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• pp.76-90
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• 2019

The purpose of this study is to analyze the survival characteristics of the restaurant business by trade area type (major and side street). By the increase of the unemployment rate, the new foundation of selt-employment type is increasing. However, due to high competition and economic recession, the sustainability of new foundation is not high. Therefore, in this study, survival analysis was performed considering the individual and commercial characteristics focused on the ordinary restaurants. The major findings are as follow. First, the characteristics of parcel unit and adjacent area have a significant effect on the survival. This means the micro-scopic spatial characteristics should be considered for survival in the location choice. Second, the regional economic characteristics in trade area have a significant effect on survival. Furthermore, these characteristics are different by the trade area type. Third. the development characteristics have a different effect on survival by the building usage and trade area type. Finally, regional economic characteristics have a significant effect on survival. These results are expected to be used as basic data for commercial location selection and trade area analysis system in the private and public sectors.

• Korean Journal of Radiology
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• 제23권5호
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• pp.495-499
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• 2022

• Communications for Statistical Applications and Methods
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• 제30권4호
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• pp.389-402
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• 2023

Multivariate or clustered failure time data often occur in many medical, epidemiological, and socio-economic studies when survival data are collected from several research centers. If the data are periodically observed as in a longitudinal study, survival times are often subject to various types of interval-censoring, creating multivariate interval-censored data. Then, the event times of interest may be correlated among individuals who come from the same cluster. In this article, we propose a unified linear regression method for analyzing multivariate interval-censored data. We consider a semiparametric multivariate accelerated failure time model as a statistical analysis tool and develop a generalized Buckley-James method to make inferences by imputing interval-censored observations with their conditional mean values. Since the study population consists of several heterogeneous clusters, where the subjects in the same cluster may be related, we propose a generalized estimating equations approach to accommodate potential dependence in clusters. Our simulation results confirm that the proposed estimator is robust to misspecification of working covariance matrix and statistical efficiency can increase when the working covariance structure is close to the truth. The proposed method is applied to the dataset from a diabetic retinopathy study.