• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.405-411
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• 2004

In the analysis of cancer data, it is important to make inferences of survival function and to assess the effects of covariates. Cox's proportional hazard model(PHM) and Beran's nonparametric method are generally used to estimate the survival function with covariates. We adjusted the incomplete survival time using the Buckley and James's(1979) pseudo random variables, and then proposed the estimator for the conditional survival function. Also, we carried out the simulation studies to compare the performances of the proposed method.

• Journal of Korea Planning Association
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• v.54 no.2
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• pp.5-16
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• 2019

The purpose of this study is to analyze the spatial characteristics of business-type-changed parcel in the Hongik-University commercial area, from the view point of commercial gentrification. A commercial gentrification occurs through a business-type-change in a spatial basic unit (microscopic spatial unit such as parcel) of an area which has not been considered in relavent policies and research. So, this study analyzed the spatial characteristics of business-type-changed parcels using the Cox's proportional hazard regression model. The main results of this study are as follows. First, as new developments in the adjacent area occur, the business-type-change probability increases. Second, by the commercial area division, the business-type-change probability is different. Finally, the accessibility is better, the probability is higher. These results could suggest that a consideration of the spatial characteristics form microscopic viewpoint is necessary to understand the commercial gentrification. And these could be used as basic data for a gentrification diagnostic and management system, which can predict gentrification from the view point of business-type-change on the basis of a parcel.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.611-620
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• 2018

Limitations on human and material resources make it is difficult to conduct Ammunition Stockpile Reliability Program (ASRP) tasks for the entire ammunition. Stockpile ammunition life prediction studies can contribute to efficient ASRP tasks. This study assess the shelf-life of ammunition, using survival analysis based on ASRP results for 60mm and 81mm mortar ammunition from 2003 to 2016. Traditional assessments often use solely storage duration as the only main independent variable; however, this assessment used other factors such as ammunition magazine shape and weather factors with the stockpile shelf-life as independent variables to conduct a Cox's proportional hazard model analysis. This was then followed by an assessment of ammunition magazine type, maximum temperature and rainfall factors influence on the shelf-life of 60mm and 81mm mortar ammunition. As a result, the type of ammunition magazine, maximum temperature and the rainfall influence the shelf-life of 60mm and 81mm mortar ammunition.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.959-975
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• 2012

Each year research institutions such as the Korea Employment Information Service(KEIS), a government institution established for the advancement of employment support services, and Job Korea, a popular Korean job website, announce first job waiting times after college graduation. This provides useful information understand and resolve youth unemployment problems. However, previous reports deal with the time as a completely observed one and are not appropriate. This paper proposes a new study on first job waiting times after college graduation set to 4 months prior to graduation. In Korea, most college students hunt for jobs before college graduation in addition, the full-fledged job markets also open before graduation. In this case the exact waiting time of college graduates can be right-censored. We apply a Cox proportional hazards model to evaluate the associations between first job waiting times and risk factors. A real example is based on the 2008 Graduates Occupational Mobility Survey(GOMS).

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.265-269
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• 2005

Cox's proportional hazards model (PHM) has been widely applied in the analysis of lifetime data, and it can be characterized by the baseline hazard function and covariates influencing systems' lifetime, where the covariates describe operating environments (e.g. temperature, pressure, humidity). In this article, we consider the constant baseline hazard function and a discrete random variable of a covariate. The estimation procedure is developed in a parametric framework when there are not only complete data but also incomplete one. The Expectation-Maximization (EM) algorithm is employed to handle the incomplete data problem. Simulation results are presented to illustrate the accuracy and some properties of the estimation results.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.285-294
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• 2016

In general, employment duration is influenced by the individual characteristics (level-1) as well as type of the occupational characteristics (level-2). That is, the data has hierarchical structure in the sense that individual employment duration is influenced by the individual-level variables (level-1) and the job-level (level-2) variables. In this paper, we study the determinants of the employment duration of youth-intern in the SMEs (small and medium enterprises) using Cox's mixed effect model. Major results at level-1 variables are as followings. First, the hazard rate of treatment group is lower than that of control group. Second, the hazard rate of woman is lower than that of man. Also, the hazard rate is lower, for the older and the workers working in the bigger company. Investigation of level-2 variables has shown that random effect for job-level is statistically significant.

• Industry Promotion Research
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• v.5 no.1
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• pp.1-11
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• 2020

The purpose of this study is to analyze the industrial accidents data with survival model. EDA approach is used to explore the relationship between two variables and among three variables for the past 10 years of industrial accidents data. Survival models are also tried. Survival curve drops more rapidly for the business with fewer employees as time goes by. Industrial accidents occur more often as the total number of industrial accidents gets larger and as the number of employees gets smaller. Agriculture, fishing and forestry have a higher level of industrial accidents than construction while service industry and 'transportation·storage and telecommunication' have a fewer number of industrial accidents than construction. Korea Safety and Health Agency's and Ministry of Employment and Labor's involvement were not effective but Civilian's was. Recurrent event data analysis reveals all most the same result as for non-recurrent data analysis.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9453-9458
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• 2014

Background: Breast cancer is the second leading cause of cancer death for women in the United States. Differences in survival of breast cancer have been noted among racial and ethnic groups, but the reasons for these disparities remain unclear. This study presents the characteristics and the survival curve of two racial and ethnic groups and evaluates the effects of race on survival times by measuring the lifetime data-based half-normal model. Materials and Methods: The distributions among racial and ethnic groups are compared using female breast cancer patients from nine states in the country all taken from the National Cancer Institute's Surveillance, Epidemiology, and End Results cancer registry. The main end points observed are: age at diagnosis, survival time in months, and marital status. The right skewed half-normal statistical probability model is used to show the differences in the survival times between black Hispanic (BH) and black non-Hispanic (BNH) female breast cancer patients. The Kaplan-Meier and Cox proportional hazard ratio are used to estimate and compare the relative risk of death in two minority groups, BH and BNH. Results: A probability random sample method was used to select representative samples from BNH and BH female breast cancer patients, who were diagnosed during the years of 1973-2009 in the United States. The sample contained 1,000 BNH and 298 BH female breast cancer patients. The median age at diagnosis was 57.75 years among BNH and 54.11 years among BH. The results of the half-normal model showed that the survival times formed positive skewed models with higher variability in BNH compared with BH. The Kaplan-Meir estimate was used to plot the survival curves for cancer patients; this test was positively skewed. The Kaplan-Meier and Cox proportional hazard ratio for survival analysis showed that BNH had a significantly longer survival time as compared to BH which is consistent with the results of the half-normal model. Conclusions: The findings with the proposed model strategy will assist in the healthcare field to measure future outcomes for BH and BNH, given their past history and conditions. These findings may provide an enhanced and improved outlook for the diagnosis and treatment of breast cancer patients in the United States.

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.187-197
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• 2024

In this study, we aimed to identify the factors influencing post-fire mortality in Korean red pine (Pinus densiflora) using Cox's proportional hazards model and analyze the impact of these factors. We monitored the mortality rate of fire-damaged pine trees for seven years after a forest fire. Our survival analysis revealed that the risk of mortality increased with higher values of the delta normalized difference vegetation index (dNDVI), delat normalized burn ratio (dNBR), bark scorch index (BSI), bark scorch height (BSH) and slope. Conversely, the risk of mortality decreased with higher elevation, greater diameter at breast height (DBH), and higher value of delta moisture stress index (dMSI) (p < 0.01). Verification of the proportional hazards assumption for each variable showed that all factors, except slope aspect, were suitable for the model and significantly influenced fire occurrence. Among the variables, BSI caused the greatest change in the survival curves (p < 0.0001). The environmental change factors determined through remote sensing also significantly influenced the survival rates (p < 0.0001). These results will be useful in establishing restoration plans considering the potential mortality risk of Korean red pine after a forest fire.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.529-538
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• 2018

Tuberculosis causes high morbidity and mortality. However, Korea still has the highest tuberculosis (TB) incidence and mortality among OECD countries despite decreasing incidence and mortality due to the development of modern medicine. Korea has now implemented various policy projects to prevent and control tuberculosis. This study analyzes the effects of public-private mix (PPM) tuberculosis control program on treatment outcomes and identifies the factors that affecting the success of TB treatment. We analyzed 130,000 new tuberculosis patient cohort from 2012 to 2015 using data of tuberculosis patient reports managed by the Disease Control Headquarters. A cumulative incidence function (CIF) compared the cumulative treatment success rates for each factor. We compared the results of the analysis using two popular types of competition risk models (cause-specific Cox's proportional hazards model and subdistribution hazard model) that account for the main event of interest (treatment success) and competing events (death).