• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1591-1598
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• 2014

The reviews of the balance sheet of commercial banks showed that loan item constitutes the largest portion of bank's assets. Although the sector has highest rate of profit, it possesses the greatest risk. Identifying factors that can contribute in lifting-up the loan repayment rate of customers of Hawassa district commercial bank is the major goal of this study. A sample of 183 customers who took loan from October, 2005 to April, 2012 was taken from the bank record. Kaplan-Meier estimation method and univariate Cox proportional hazard model were applied to identify factors affecting bank loan repayment rate. The result from Kaplan-Meier survival estimation revealed that the loan repayment rate is significantly related with loan type, and previous loan experience, educational level and mode of repayment. The log-rank test indicates that the survival probability of loan customers is not statistically different in repaying the loan among groups classified by sex. Moreover, the univariate Cox proportional hazard model result portrayed that educational level, having previous loan experience, mode of repayment, collateral type and purpose of loan are significantly related with loan repayment rate of customers commercial bank. Hence, banks should design loan strategies giving special emphasis on the significant factors while they are giving loans to their customers.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.647-658
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• 2018

In this paper, we study statistical inferences on the maximum likelihood estimation of a normal distribution when data are randomly censored. Likelihood equations are derived assuming that the censoring distribution does not involve any parameters of interest. The maximum likelihood estimators (MLEs) of the censored normal distribution do not have an explicit form, and it should be solved in an iterative way. We consider a simple method to derive an explicit form of the approximate MLEs with no iterations by expanding the nonlinear parts of the likelihood equations in Taylor series around some suitable points. The points are closely related to Kaplan-Meier estimators. By using the same method, the observed Fisher information is also approximated to obtain asymptotic variances of the estimators. An illustrative example is presented, and a simulation study is conducted to compare the performances of the estimators. In addition to their explicit form, the approximate MLEs are as efficient as the MLEs in terms of variances.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.32-38
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• 2021

This paper suggests an approach to evaluate the reliability of an intelligent power module with information deficiency of prior distribution and the characteristics of censored data through Bayesian statistics. This approach used a prior distribution of Bayesian statistics using the lifetime information provided by the manufacturer and compared and evaluated diffuse prior (vague prior) distributions. To overcome the computational complexity of Bayesian posterior distribution, it was computed with Gibbs sampling in the Monte Carlo simulation method. As a result, the standard deviation of the prior distribution developed using simple information was smaller than that of the posterior distribution calculated with the diffuse prior. In addition, it showed excellent error characteristics on RMSE compared with the Kaplan-Meier method.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.130-142
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• 2018

Purpose: The purpose of this study is to introduce regression method in the presence of competing risks and to show how you can use the method with hypothetical data. Methods: Survival analysis has been widely used in biostatistics division. But the same method has not been utilized in reliability division. Especially competing risks, where more than a couple of 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 utilized in the area of reliability or they are analysed in the wrong way. Specifically Kaplan-Meier method 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. In addition, sample competing risks data are analysed using cumulative incidence function along with some graphs. Lastly we compare cumulative incidence functions with regression type analysis briefly. Results: We used cumulative incidence function to calculate the survival probability or failure probability in the presence of competing risks. We also drew some useful graphs depicting the failure trend over the lifetime. Conclusion: This research shows that Kaplan-Meier method is not appropriate for the evaluation of survival or failure over the course of lifetime in the presence of competing risks. Cumulative incidence function is shown to be useful in stead. Some graphs using the cumulative incidence functions are also shown to be informative.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.761-769
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• 2018

Simulations are important for survival analyses that deal with censored data. Cox models are widely used in survival analyses, therefore, we investigate how to generate censored data that can simulate the Cox model. Bender et al. (Statistics in Medicine, 24, 1713-1723, 2005) provided a parametric method for generating survival times, but we need to generate censoring times as well as survival times to simulate the censored data. In addition to the parametric method for generating censored data, a nonparametric method is also proposed and applied to a real data set.

• Vascular Specialist International
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• v.34 no.4
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• pp.88-93
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• 2018

Purpose: This study aimed to compare surgical revisions and balloon angioplasty after surgical thrombectomy on thrombosed dialysis access as a first event. Materials and Methods: Records of patients undergoing creation of arteriovenous grafts (AVGs) at the Gachon University Gil Medical Center between March 2008 and February 2016 were reviewed. Among them, patients who underwent treatment on first-time thrombotic occlusion after AVG creation were identified. Outcomes were primary, primary-assisted, and secondary patency. The patency was generated using the Kaplan-Meier method, and patency rates were compared by log-rank test. Results: A total of 59 de novo interventions (n=26, hybrid interventions; n=33, surgical revisions) for occlusive AVGs were identified. The estimated 1-year primary patency rates were 47% and 30% in the surgery and hybrid groups, respectively. The estimated primary patency rates were not different between the two groups (log-rank test, P=0.73). The Kaplan-Meier estimates of 6 and 12 months for primary-assisted patency rates were 68% and 57% in the surgery group and 56% and 56% in the hybrid group. The Kaplan-Meier estimates of 12 and 24 months secondary patency rates were 90% and 71% in the surgery group and 79% and 62% in the hybrid group. There were no differences in the estimated primary-assisted and secondary patency rates between the two groups. Conclusion: Our results showed no significant difference between the two groups in terms of primary patency (P=0.73), primary-assisted patency (P=0.85), and secondary patency (P=0.78). However, percutaneous transluminal angioplasty can give more therapeutic options for both surgeons and patients.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.519-531
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• 2017

We consider goodness-of-fit test statistics for Weibull distributions when data are randomly censored and the parameters are unknown. Koziol and Green (Biometrika, 63, 465-474, 1976) proposed the $Cram\acute{e}r$-von Mises statistic's randomly censored version for a simple hypothesis based on the Kaplan-Meier product limit of the distribution function. We apply their idea to the other statistics based on the empirical distribution function such as the Kolmogorov-Smirnov and Liao and Shimokawa (Journal of Statistical Computation and Simulation, 64, 23-48, 1999) statistics. The latter is a hybrid of the Kolmogorov-Smirnov, $Cram\acute{e}r$-von Mises, and Anderson-Darling statistics. These statistics as well as the Koziol-Green statistic are considered as test statistics for randomly censored Weibull distributions with estimated parameters. The null distributions depend on the estimation method since the test statistics are not distribution free when the parameters are estimated. Maximum likelihood estimation and the graphical plotting method with the least squares are considered for parameter estimation. A simulation study enables the Liao-Shimokawa statistic to show a relatively high power in many alternatives; however, the null distribution heavily depends on the parameter estimation. Meanwhile, the Koziol-Green statistic provides moderate power and the null distribution does not significantly change upon the parameter estimation.

• Journal of Information Technology Services
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• v.18 no.4
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• pp.151-170
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• 2019

This study conducted an empirical analysis through the Kaplan-Meier method, which is mainly used for clinical experiment analysis, on the survival rate and the survival duration of small and medium-sized enterprises using B2B e-commerce guarantee provided by credit guarantee institutions for activating B2B e-commerce transactions. The variables presented in this study are analyzed by the subdivision of the survival characteristics of enterprises using B2B e-commerce guaranteee by year, enterprises attribute, representative attribute, and guarantee use amount based on the variables tested through previous studies. According to the empirical analysis, SMEs using B2B e-commerce guarantees have a higher survival rate compared to general enterprises Simply by year and have a variety of survival characteristics, and most of the variables have a significant effect except for some variables. The implication of this study is that the researches conducted on enterprises participating in B2B e-commerce for a long period of time to support the establishment of stable business environment of SMEs and the results of empirical analysis on the survival characteristics are useful information to the stakeholders of B2B e-commerce And it can contribute to enhance the survival rate of related enterprises.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.411-424
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• 2021

Inference following two-stage adaptive designs (also known as two-stage randomization designs) with survival endpoints usually focuses on estimating and comparing survival distributions for the different treatment strategies. The aim is to identify the treatment strategy(ies) that leads to better survival of the patients. The objectives of this study were to assess the performance three commonly cited methods for estimating survival distributions in two-stage randomization designs. We review three non-parametric methods for estimating survival distributions in two-stage adaptive designs and compare their performance using simulation studies. The simulation studies show that the method based on the marginal mean model is badly affected by high censoring rates and response rate. The other two methods which are natural extensions of the Nelson-Aalen estimator and the Kaplan-Meier estimator have similar performance. These two methods yield survival estimates which have less bias and more precise than the marginal mean model even in cases of small sample sizes. The weighted versions of the Nelson-Aalen and the Kaplan-Meier estimators are less affected by high censoring rates and low response rates. The bias of the method based on the marginal mean model increases rapidly with increase in censoring rate compared to the other two methods. We apply the three methods to a leukemia clinical trial dataset and also compare the results.

• Journal of the Korean Data and Information Science Society
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• v.1
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• pp.47-57
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• 1990

A method which determines the number of replications in the simulation is proposed, particularly for small-sample comparison of estimators. This method takes the smallest number of replications that makes the difference of mean square errors be statistically significant and provides an efficient algorithm for calculating the standard error of the mean square error. Two examples are illustrated, the first one is on comparison of mean and median ; the second, the Kaplan-Meier type and Buckley-James type estimators of a quantile function with censored data.