• Journal of the Korean Statistical Society
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• v.24 no.1
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• pp.197-218
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• 1995

We first consider the random censorship model of survival analysis. Efron (1981) introduced two equivalent bootstrap methods for censored data. We propose a new bootstrap scheme, called Method 3, that acts conditionally on the censoring pattern when making inference about aspects of the unknown life-time distribution F. This article contains (a) a motivation for this refined bootstrap scheme ; (b) a proof that the bootstrapped Kaplan-Meier estimatro fo F formed by Method 3 has the same limiting distribution as the one by Efron's approach ; (c) description of and report on simulation studies assessing the small-sample performance of the Method 3 ; (d) an illustration on some Danish data. We also consider the model in which the survival times are censered by death times due to other caused and also by known fixed constants, and propose an appropriate bootstrap method for that model. This bootstrap method is a readily modified version of the Method 3.

• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.359-368
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• 1998

Let ξ$_{p}$(z$_{0}$) be the pth quantile of the distribution of the survival time of an individual with time-invariant covariate vector z$_{0}$ in the additive risk model. We propose an estimator of (ξ$_{p}$(z$_{0}$) and derive its asymptotic distribution, and then construct an approximate confidence interval of ξ$_{p}$(z$_{0}$) . Simulation studies are carried out to investigate performance of the proposed estimator far practical sample sizes in terms of empirical coverage probabilities. Also, the estimator is illustrated on small cell lung cancer data taken from Ying, Jung, and Wei (1995) .d Wei (1995) .

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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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.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.245-256
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• 2000

Large sample properties of Life-Table estimator are discussed for interval censored bivariate survival data. We restrict out attention to the situation where response times within pairs are not distinguishable and the univariate survival distribution is the same for any individual within any pair.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.233-244
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• 2000

Confidence intervals for survival function give useful information about the lifetime distribution. In this paper we develop Edgeworkth expansions as approximation to the true and bootstrap distributions of normalized nonparametric maximum likelihood estimator of survival function in the Koziol-Green model and then use these results to show that the bootstrap approximations have second order accuracy.

• The Pure and Applied Mathematics
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• v.2 no.2
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• pp.83-89
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• 1995

A Bayes estimator of the survival distribution function due to Susarla and Van Ryzin(1976) is used to estimate the mth moment of a survival time on the basis of censored observations in a random censorship model. Asymptotic normality of the estimator is proved using the functional version of the delta method.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.115-121
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• 2017

This paper is to introduce the main modeling assumptions and data structures associated with right-censored data to describe the successful methodological ideas for analyzing such a field-failure-data when components operating in different environments. The Kaplan - Meier method is the most popular method used for survival analysis. Together with the log-rank test, it may provide us with an opportunity to estimate survival probabilities and to compare survival between groups. An important advantage of the Kaplan - Meier curve is that the method can take into account some types of censored data, particularly right-censoring. The above non-parametric method was used to verify the equality of parts life used in different environments. After that, we performed the life distribution analysis using the parametric method. We simulated data from three distributions: exponential, normal, and Weibull. This allowed us to compare the results of the estimates to the known true values and to quantify the reliability indices. Here we used the Akaike information criterion to find a suitable life time distribution. If the Akaike information criterion is the smallest, the best model of failure data is presented. In this paper, no-nparametrics and parametrics methods are analyzed using R program which is a popular statistical program.

• Computers and Concrete
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• v.21 no.3
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• pp.291-298
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• 2018

In this study, the flexural fatigue performance of concrete beams made with 100% Coarse Recycled Concrete Aggregates (RCA) and 100% Coarse Natural Aggregates (NA) were statistically commanded. For this purpose, the experimental fatigue test results of earlier researcher were investigated using two parameter Weibull distribution. The shape and scale parameters of Weibull distribution function was evaluated using seven numerical methods namely, Graphical method (GM), Least-Squares (LS) regression of Y on X, Least-Squares (LS) regression of X on Y, Empherical Method of Lysen (EML), Mean Standard Deviation Method (MSDM), Energy Pattern Factor Method (EPFM) and Method of Moments (MOM). The average of Weibull parameters was used to incorporate survival probability into stress (S)-fatigue life (N) relationships. Based on the Weibull theory, as single and double logarithm fatigue equations for RCA and NA under different survival probability were provided. The results revealed that, by considering 0.9 level survival probability, the theoretical stress level corresponding to a fatigue failure number equal to one million cycle, decreases by 8.77% (calculated using single-logarithm fatigue equation) and 6.62% (calculated using double logarithm fatigue equation) in RCA when compared to NA concrete.

• Korean Journal of Head & Neck Oncology
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• v.18 no.2
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• pp.179-183
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• 2002

Objective: A comparison of American Joint Committee on Cancer (AJCC) 1988 and 1997 nasopharyngeal carcinoma (NPC) classifications was made in terms of patient distribution and efficacy in predicting prognosis. Materials and Methods: Between Jan. 1981 and Dec. 1998, 60 cases of node negative nasopharyngeal carcinoma were retrospectively reviewed. The extent of disease each patients restaged according to the 4th and 5th AJCC system and Ho system, respectively. Results: The overall and disease free 5-year survival rates were 61.1% and 62.6%, respectively. Among T classifications of 4th AJCC, 5th AJCC and Ho staging system were not observed significantly different in disease-free survival rates, respectively. Conclusion: We observed a better patient distribution with AJCC 1997 comparing to AJCC 1988. The new classification also attained better statistical significances among stages in the overall survival and disease free survival rates was needed.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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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.