• Smart Media Journal
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• v.9 no.4
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• pp.126-133
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• 2020

The treatment policy and prognosis are determined based on the final stage of lung cancer patients. The final stage of lung cancer patients is determined based on the T, N, and M stage classification table provided by the American Cancer Society (AJCC). However, the final stage of AJCC has limitations in its use for various fields such as patient treatment, prognosis and survival days prediction. In this paper, clustering algorithm which is one of non-supervised learning algorithms was assessed in order to check whether using only T, N, M stages with a data science method is effective for classifying the group of patients in the aspect of survival days. The final stage groups and T, N, M stage clustering groups of lung cancer patients were compared by using the cox proportional hazard model. It is confirmed that the accuracy of prediction of survival days with only T, N, M stages becomes higher than the accuracy with the final stages of patients. Especially, the accuracy of prediction of survival days with clustering of T, N, M stages improves when more or less clusters are analyzed than the seven clusters which is same to the number of final stage of AJCC.

• Korean Journal of Social Welfare
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• v.61 no.3
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• pp.307-328
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• 2009

This study aims to investigate the patterns and causes of the marital duration. Data used for this study are ten waves of Korean Labor and Income Panel Study(KLIPS) in 1998~2007, in which the final sample consists of 2,397 households. The Life-table method is used for describing the overall patterns of marital duration by birth-cohorts and different education groups, and the Cox proportional hazard regression model is used to identify significant factors on the marital duration. The results show that among the all respondents, the 0.79% has divorced or separated within five years after marriage, 2.12% within 10 years, and 5.84% within 20 years, respectively. In addition, the Cox regression results show that the marital duration is significantly affected by the birth-cohorts of respondents and their spouses, education level, earning of spouses, co-residence with parents, and household income. This implies that the hazard rate of marital disruption is higher for younger cohorts, individuals with lower education and economic status, persons living with parents-in-law, compared to their counterparts. Thus, it is necessary to implement social welfare policies applicable for these persons.

• Korea journal of population studies
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• v.29 no.3
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• pp.159-188
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• 2006

This study attempts to create a longitudinal dataset by linking tdata on the identical individuals across the monthly sample household management lists of the Economically Active Population Survey(EAPS) and the Household Income and Expenditure Survey(HIES). Using the data constructed through such process, the study also tryies to analyze the duration of longitudinal responses and the characteristics of nonrespondents. Between 1998 and 2002, longitudinal response rates had declined to 46% of total EAPS and 34% of total HIES. The fact that nonresponse was not a random phenomenon leads to concerns about the representativeness of the remaining sample. Using Cox's proportional hazard model the study revealed that the duration of longitudinal responses is affected by the ownership of house and the age of the respondent.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.771-783
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• 2018

The life insurance industry is interested in various factors that influence the long-term extensions of insurance contracts such as the necessity for the advisors' long-term management of consumers, product consulting, and improvement of the investment aspects. This paper investigates important factors leading to a long-term contract that forms an important part of the life insurance industry in Korea. For this purpose we used the data of contents (i.e., data from Jan 1, 2011 to Dec 31, 2016) of the contracts of xxx insurance company. In this paper, we present how to select important variables to influence the duration of the contract maintenance via a penalized Cox's proportional hazards (PH) modelling approach using insurance life data. As the result of analysis, we found that the selected important factors were the advisor's status, the reward type 2 (annuity insurance) and tendency 4 (safety-pursuing type).

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.287-295
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• 2019

This study was conducted to analyze firm survival rate and impact factors of survival of Foreign-invested Companies in Korea which is between 2006 and 2017. An empirical analysis of the survival factors of firms used explanatory variables such as characteristics of the and 3 firm dummy and 2 firm factors, financial variables of 3 profitability and 3 stability factors. The Kaplan-Meier method was chosen to perform analyses on the survival rates, Cox Proportional Hazard Model took to conduct on the impact factors. As a result of the impact factors of Foreign-invested Companies survival, Ownership (OS), Labour (NE ) of characteristics of the firm had positive effects. The Gross Sales Profit (GSP), Net Profit (NP ) and Operating Profit (OP ) of the financial characteristics had a positive effect. Additional Asset (LA ) had positive effects and Capital (LC), Debt (LB ) had a negative effect. Other factors did not produce significant results.

• Korean Journal of Social Welfare
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• v.39
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• pp.210-237
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• 1999

The primary purpose of this study is to empirically examine the determinants of reemployment of the unemployed after the crash of Korea's economy in 1997. This study also investigates the effects of the government unemployment programs on reemployment of the program beneficiaries. Using the data from the 1998 Survey on Unemployment Condition and Welfare Needs, co-directed by the Korea Institute of Health and Welfare and the Korea Institute of Labor Policy, a Cox regression analysis was conducted. The study results suggested that, in general, the government unemployment programs did not have noticeable effects on reemployment of the beneficiaries. The study, however, found that the effect of the government programs varied, depending on the mode of unemployment-exit, that is, full-time versus part-time reemployment. In addition, the effects of such factors on reemployment as socio-economic characteristics of the unemployed, characteristics of households with unemployed family members, and previous job characteristics are also examined. Based on the study findings, some policy implications are discussed, and suggestions are made for improving the current unemployment programs.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• Korean small business review
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• v.43 no.3
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• pp.1-20
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• 2021

The survival period according to technological capability was analyzed for about 22,500 innovative SMEs in the service industry. The survival period was defined as the occurrence of overdue and default, and the technological capability was divided into two clusters. As a result of estimating the survival period according to technological capability through Kaplan-Meier analysis, it was confirmed that the estimated survival period of T1-T4 grade service innovative SMEs was significantly greater in both overdue and default. As a result of the analysis of the Cox proportional hazard model applying the control variable, it was confirmed that the higher technological capability, the lower the risk in the group of start-up companies. However, in the group of non-start-up companies the technological capability did not significantly affect the survival period, and the influence of the variables related to the size of the company was found to increase. Therefore, the technological capability is meaningful as additional information that has a significant effect on the survival period of innovative SMEs in the start-up companies group of service industry. In addition, it was concluded that it is necessary to reflect the technological capability when establishing the SME support and promotion policy of the start-up companies group in the service industry.

• Korean Journal of School Psychology
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• v.18 no.1
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• pp.31-48
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• 2021

The purpose of this study was to determine whether the retention of university freshmen could be predicted using their peer relationships in a specific department. In this study, retention was defined as a student staying enrolled in their university for a certain period of time. Social relationships are formed through interaction between people, so both students' self-perceptions and others' perceptions of them must be accounted for, so we used a social network analysis that did so. We examined social networks visualizations that allowed for a rich interpretation of numerical information. Participants in this study were freshmen who enrolled in an undergraduate program in 2017, 2018, or 2019. We used the name generator method to determine how quantitative friendship network variables predicted the academic retention up to the first semester of 2020. Cox proportional hazard model analysis showed that the weighted indegree centrality with intimacy positively predicted retention. The results of this study can be used to identify and conduct interventions for students who may be likely to disenroll. However all of the students did not participate in the department, it was difficult to examine their entire peer networks. Thus, this study's results cannot be generalized because the participants are students of a specific major, so further research is needed to produce more generalizable results.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.27-40
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• 2023

This study analyzes the factors affecting the survival of young start-up companies. A youth start-up company was defined as a company with a founder's age under 39. The study was based on evaluation data from 3,540 companies evaluated by the Technology Guarantee Fund to support youth start-up guarantees during the period from 2012 to 2015. In this study, independent variables were defined as founder characteristics, start-up environment, and start-up strategy, and entrepreneurship, knowledge level, and development capabilities were set as variables for start-up characteristics, competition conditions and comparative advantage with alternatives in the start-up environment, and item novelty, commercialization plan and financing plan were set as variables. For variable measurement, the evaluation index of the youth start-up evaluation model of the Technology Guarantee Fund was used. Management performance was defined as the survival of a company, and the survival of 12, 36, 60, and 84 months was measured based on the occurrence of insolvency registered by the Korea Technology Guarantee Fund. The Cox proportional risk model was used for hypothesis testing. As a result of the analysis, knowledge level and development capability were statistically significant in the characteristics of the founder, and the financing plan in the start-up strategy was statistically significant regardless of the survival period. Among the start-up strategies, the novelty of the item had a positive effect on survival after 36 months. Entrepreneurship was significant only in 12-month survival. The most important order for survival was identified in the order of financing plan, knowledge level, item novelty and development capability, of which the founder's knowledge level in the beginning and the funding plan in the second half had the greatest impact.