• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.685-694
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• 1998

임상실험이나 신뢰성공학 분야에서 임의 중단자료를 이용한 비모수적 신뢰도 추정량으로 Kaplan-Meier 추정량과 Nelson형 추정량이 많이 사용되고 있다. 그러나 Nelson형 추정량은 평균제곱오차의 관점에서 Kaplan-Meier 추정량보다 추정능력이 우수한 반면 편의는 신뢰도가 감소함에 따라 양의 방향으로 점증하는 소표본 특성을 갖는다. Nelson형 추정량의 이러한 특성 때문에 신뢰도의 함수로 표현되는 잔여수명 분위수함수 등의 추정시에는 평균제곱오차의 관점에서 Kaplan-Meier 추정량보다 추정능력이 떨어짐을 볼 수 있다. 이러한 점을 고려하여 이 두 추정량을 가중평균으로 통합한 새로운 비모수적 신뢰도 추정량을 제안하고 추정량의 특성을 비교 분석하였다.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.957-968
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• 2021

Inverse censoring probability weighting (ICPW) is a popular technique in survival data analysis. In applications of the ICPW technique such as the censored regression, it is crucial to accurately estimate the censoring probability. A simulation study is undertaken in this article to see how censoring probability estimate influences model performance in censored regression using the ICPW scheme. We compare three censoring probability estimators, including Kaplan-Meier (KM) estimator, Cox proportional hazard model estimator, and local KM estimator. For the local KM estimator, we propose to reduce the predictor dimension to avoid the curse of dimensionality and consider two popular dimension reduction tools: principal component analysis and sliced inverse regression. Finally, we found that the Cox proportional hazard model estimator shows the best performance as a censoring probability estimator in both mean and median censored regressions.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.56-63
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• 2016

Purpose: The purpose of this study is to point out that the Kaplan-Meier method is not valid to calculate the survival probability or failure probability (risk) in the presence of competing risks and to introduce more valid method of cumulative incidence function. Methods: Survival analysis methods have been widely used in biostatistics division. However the same methods have not been utilized in reliability division. Especially competing risks cases, where several causes of failure occur and the occurrence of one event precludes the occurrence of the other events, are scattered in reliability field. But they are not noticed in the realm of reliability expertism or they are analysed in the wrong way. Specifically Kaplan-Meier method which assumes that the censoring times and failure times are independent is used to calculate the probability of failure in the presence of competing risks, thereby overestimating the real probability of failure. Hence, cumulative incidence function is introduced and sample competing risks data are analysed using cumulative incidence function and some graphs. Finally comparison of cumulative incidence functions and regression type analysis are mentioned briefly. Results: Cumulative incidence function is used to calculate the survival probability or failure probability (risk) in the presence of competing risks and some useful graphs depicting the failure trend over the lifetime are introduced. Conclusion: This paper shows that Kaplan-Meier method is not appropriate for the evaluation of survival or failure over the course of lifetime. In stead, cumulative incidence function is shown to be useful. Some graphs using the cumulative incidence functions are also shown to be informative.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.67-78
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• 2015

The objective of this paper is to analyze survival rate and factors of FDI(Foreign direct investment) using FDI data of Ministry of Knowledge and Economy. Kaplan-Meier estimation was used. The result was as follows. M&A of FDI was much more risk than Greenfield FDI. .FDI to the IT-service industry was much more risk than FDI to the manufacturing industry. Partnership under 50% was much more risk than partnership over 50%. The accumulated survival rate of M&A was higher then Greenfield until fourth period but was lower than Greenfield after fourth period. The accumulated survival rate of M&A was lower than others from the first period to last period. There was no difference between Partnership under 50% and partnership over 50% to 4th period. After 4th period, Accumulated survival rate of partnership under 50% was higher than accumulated survival partnership over 50%.

• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.225-233
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• 2000

In life-testing experiments, in which the longest time an experimental unit is on test is not a failure time, but rather a censored observation. For the situation the Kaplan-Meier estimator is known to be a baised estimator of the survival function. Several modifications of the Kaplan-Meier estimator are examined and compared with bias and mean squared error.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.251-255
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• 2005

중도절단된 자료와 표본수가 적은 자료를 가지는 생존분석에서 생존율을 추정하거나 두 집단의 생존율을 비교할 때 정규분포 근사를 가정한 신뢰구간을 이용하는 데는 많은 어려움이 생긴다. 생존함수의 신뢰구간에 대한 중도절단을, 표본의 크기에 따른 다양한 상황의 모의실험을 통하여 Kaplan-Meier, Nelson, 적률 추정량 그리고 cox model의 ${\beta}$을 가지고 붓스트랩을 이용한 신뢰구간과 비모수 신뢰구간, 우도비 신뢰구간의 실제 포함 확률을 비교해보고자 한다.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.311-319
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• 2012

The simplest and the most important distribution in survival analysis is exponential distribution. Koziol and Green (1976) derived Cram$\acute{e}$r-von Mises statistic's randomly censored version based on the Kaplan-Meier product limit estimate of the distribution function; however, it could not be practical for a real data set since the statistic is for testing a simple goodness of fit hypothesis. We generalized it to the composite hypothesis for exponentiality with an unknown scale parameter. We also considered the classical Kolmogorov-Smirnov statistic and generalized it by the exact same way. The two statistics are compared through a simulation study. As a result, we can see that the generalized Koziol-Green statistic has better power in most of the alternative distributions considered.

• Journal of Chest Surgery
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• v.32 no.1
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• pp.27-31
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• 1999

Background: In spite of the development of chemotherapy, prognosis of metastatic lung cancer was poor. On the other hand, surgical intervention has proven itself to bring out superior results, therefore more operations are being praticed based on this superiority against chemotherapy and other modalities on metastatic lung cancer. Material and Method : We analyzed the surgical cases performed from 1983 to 1997 on 17 cases and estimated 5 year survival rate using Kaplan-Meier method. Result: Average age was 42.8, ratio between male and female was 10:7. We had 8 single lobe resections,3 pneumonectomies,1 wedge resection,2 bilobectomy and 3 cases of lobar resection with wedge resection. 5 deaths have occured and among the 5, 3 patients were caused by recurrence of ca. The remaining 12 patients are being followed up in OPD basis among these, 3 recurrence were observed and 9 are still free of cancer. The average survival time was 40.5 months and 5 year survival rate obtained through the Kaplan-Meier method was 60.4%. Conclusion: Even though we are a bit short of cases, we recommend that a thoracic surgeon approach this disease through a surgical method as possibly as he could.

• Knowledge Management Research
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• v.11 no.2
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• pp.95-109
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• 2010

The objectives of this study are to identify the survival function (hazard function) of small and medium enterprises by using technology rating data for the companies guaranteed by Korea Technology Finance Corporation (KOTEC), and to figure out the factors that affects their survival. To serve the purposes, this study uses Kaplan-Meier Analysis as a non-parametric method and Cox proportional hazards model as a semi-parametric one. The 17,396 guaranteed companies that assessed from July 1st in 2005 to December 31st in 2009 are selected as samples (16,504 censored data and 829 accident data). The survival time is computed with random censoring (Type III) from July in 2005 as a starting point. The results of the analysis show that Kaplan-Meier Analysis and Cox proportional hazards model are able to readily estimate survival and hazard function and to perform comparative study among group variables such as industry and technology rating level. In particular, Cox proportional hazards model is recognized that it is useful to understand which technology rating items are meaningful to company's survival and how much they affect it. It is considered that these results will provide valuable knowledge for practitioners to find and manage the significant items for survival of the guaranteed companies through future technology rating.

• Journal of Korean Critical Care Nursing
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• v.3 no.2
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• pp.1-11
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• 2010

Purpose: This study was designed to identify the factors affecting healing of Stage 2 pressure ulcer in an acute care facility in Korea. Methods: 286 Stage 2 pressure ulcers of 145 patients were examined. Data were collected in the period between October $1^{st}$, 2006 and September $30^{th}$, 2007. Data were analyzed with Kaplan-Meier survival analysis for cumulative recovery rate of Stage 2 pressure ulcers. Cox proportional hazard model was used to examine effects of multiple variables simultaneously. Results: Out of 286 initial Stage 2 pressure ulcers, 204 (71.3%) pressure ulcers healed completely. The median time to heal was 15 days according to Kaplan-Meier survival analysis. Cox proportional hazard model showed that the Stage 2 pressure ulcers healed more quickly when pressure redistribution surfaces were used (p<.001, HR=2.184), patients were administered with vitamins (p= .038, HR=1.451), and the size of the pressure ulcers were small (${\leq}3.0cm^2$, p= .006, HR=1.765). Conclusion: The factors contributing to the healing of Stage 2 pressure ulcer in an acute care setting were the application of pressure redistribution surface, small ulcer size (${\leq}3.0cm^2$), and the administration of vitamins.