• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.9-20
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• 1990

The purpose of this paper is to propose the modified semiparametric estimators for survival function in the Cox's regression model with randomly censored data based on Tsiatis and Breslow estimators, and present their asymptotic variances estimates. The proposed estimators are compared to Tsiatis, Breslow, and Kaplan-Meier estimators through a small-sample Monte Carlo study. The simulation results show that the proposed estimators are preferred for small sample sizes.

• Clinics in Shoulder and Elbow
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• v.16 no.1
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• pp.63-72
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• 2013

In medical research, multivariate analysis, especially multiple regression analysis, is used to analyze the influence of multiple variables on the result. Multiple regression analysis should include variables in the model and the problem of multi-collinearity as there are many variables as well as the basic assumption of regression analysis. The multiple regression model is expressed as the coefficient of determination, $R^2$ and the influence of independent variables on result as a regression coefficient, ${\beta}$. Multiple regression analysis can be divided into multiple linear regression analysis, multiple logistic regression analysis, and Cox regression analysis according to the type of dependent variables (continuous variable, categorical variable (binary logit), and state variable, respectively), and the influence of variables on the result is evaluated by regression coefficient${\beta}$, odds ratio, and hazard ratio, respectively. The knowledge of multivariate analysis enables clinicians to analyze the result accurately and to design the further research efficiently.

• Journal of the Korean Wood Science and Technology
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• v.12 no.3
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• pp.3-8
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• 1984

It is shown that Paul and Jones' Rule of Mixtures modified by Smith and Cox's theory can be used for the fiber-reinforced, sulfur-based composites, when the constant for the linear regression equation is given. The computation results, programmed by Hewlett Packard 75C (HP 75C) using math rom pack for the linear regression form, expressed as $E_c=\frac{1}{3}aE_fV_f+bE_mV_m$, turn out to be a=3.27-3.54 b=-2.47~-2.80. This results indicate that the factors such as density of fiber mat and the amount of matrix used have nothing for affecting the numerical value of the constants a and b of the linear regression form. Conclusively this results also show that the Paul and Jones' Rule of Mixtures which has been used for the composites made by randomly-oriented long fiber can also be used for the composites made by short fiber with the same fiber orientation such as wood and lignocellulosic fibers.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.260-268
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• 2024

Cervical cancer is the fourth most common cancer in women worldwide, and more than 604,000 new cases were reported in 2020 alone, resulting in approximately 341,831 deaths. The Cox regression model is a major model widely adopted in cancer research, but considering the existence of nonlinear associations, it faces limitations due to linear assumptions. To address this problem, this paper proposes ResSurvNet, a new model that improves the accuracy of cervical cancer mortality prediction using ResNet's residual learning framework. This model showed accuracy that outperforms the DNN, CPH, CoxLasso, Cox Gradient Boost, and RSF models compared in this study. As this model showed accuracy that outperformed the DNN, CPH, CoxLasso, Cox Gradient Boost, and RSF models compared in this study, this excellent predictive performance demonstrates great value in early diagnosis and treatment strategy establishment in the management of cervical cancer patients and represents significant progress in the field of survival analysis.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.97-101
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• 2012

Objective: With the background of aging population in China and advances in clinical medicine, the amount of operations on old patients increases correspondingly, which imposes increasing challenges to critical care medicine and geriatrics. The study was designed to describe information on the length of ICU stay from a single institution experience of old critically ill gastric cancer patients after surgery and the framework of incorporating data-mining techniques into the prediction. Methods: A retrospective design was adopted to collect the consecutive data about patients aged 60 or over with a gastric cancer diagnosis after surgery in an adult intensive care unit in a medical university hospital in Shenyang, China, from January 2010 to March 2011. Characteristics of patients and the length their ICU stay were gathered for analysis by univariate and multivariate Cox regression to examine the relationship with potential candidate factors. A regression tree was constructed to predict the length of ICU stay and explore the important indicators. Results: Multivariate Cox analysis found that shock and nutrition support need were statistically significant risk factors for prolonged length of ICU stay. Altogether, eight variables entered the regression model, including age, APACHE II score, SOFA score, shock, respiratory system dysfunction, circulation system dysfunction, diabetes and nutrition support need. The regression tree indicated comorbidity of two or more kinds of shock as the most important factor for prolonged length of ICU stay in the studied sample. Conclusions: Comorbidity of two or more kinds of shock is the most important factor of length of ICU stay in the studied sample. Since there are differences of ICU patient characteristics between wards and hospitals, consideration of the data-mining technique should be given by the intensivists as a length of ICU stay prediction tool.

• The Journal of Korean Academy of Prosthodontics
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• v.45 no.1
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• pp.48-59
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• 2007

Statement of problems: There are few studies which reported the survival rates of the specific dental implant systems in the Korean population with the follow-up periods longer than 5 years. Purpose: This retrospective clinical study was aimed to evaluate cumulative survival rate (CSR) of $Br{\aa}nemark$ implants followed for 10 years and to determine risk factors for implant failure. Material and methods: A total of 271 $Br{\aa}nemark$ implants in 83 patients were investigated with several identified risk factors. Life table analysis was undertaken to examine the CSR. Cox regression method was conducted to assess the association between potential risk factors and overall CSR. Results: Thirty implants failed. The 10-year implant CSR was 82.5%. Cox regression analysis demonstrated a significant predictive association between overall CSR and implant length (P<.05). Conclusion: An acceptable long-term result of $Br{\aa}nemark$ implant was achieved and implant length showed a significant association with the CSR.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.283-290
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• 2014

In the flat panel display industry, to meet production target quantities and the deadline of production, the scheduler and dispatching systems are major production management systems which control the order of facility production and the distribution of WIP (Work In Process). Especially the delivery time is a key factor of the dispatching system for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors of the delivery time and to build the delivery time forecasting model. To select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the accelerated failure time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the mean square error (MSE) criteria, the AFT model decreased by 33.8% compared to the statistics prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing the delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

• Korean Business Review
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• v.14
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• pp.45-62
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• 2001

This study examines the factors that affect longevity of strategic alliances, highlighting environmental volatility, nationality, and previous experience with strategic alliances. In general, successful strategic alliances are more likely to continue to exist than unsuccessful ones. Therefore, it is argued that studying on factors affecting the continuance of strategic alliances indirectly confirms the factors of success and failure in strategic alliances. In order to conduct this study, the needed data were collected from CATI(Cooperative Agreements and Technology Indicators) Data Base, which was gathered by a group of researchers in the University of Limburg in the Netherlands. Cox's Regression was used to analyze the data. Implications for research and practice are discussed.

• Acute and Critical Care
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• v.33 no.4
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• pp.230-237
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• 2018

Background: Socioeconomic status (SES) is closely associated with health outcomes, including mortality in critically ill patients admitted to intensive care unit (ICU). However, research regarding this issue is lacking, especially in countries where the National Health Insurance System is mainly responsible for health care. This study aimed to investigate how the SES of ICU patients in South Korea is associated with mortality. Methods: This was a retrospective observational study of adult patients aged ${\geq}20$ years admitted to ICU. Associations between SES-related factors recorded at the time of ICU admission and 30-day and 1-year mortalities were analyzed using univariable and multivariable Cox regression analyses. Results: A total of 6,008 patients were included. Of these, 394 (6.6%) died within 30 days of ICU admission, and 1,125 (18.7%) died within 1 year. Multivariable Cox regression analysis found no significant associations between 30-day mortality after ICU admission and SES factors (P>0.05). However, occupation was significantly associated with 1-year mortality after ICU admission. Conclusions: Our study shows that 30-day mortality after ICU admission is not associated with SES in the National Health Insurance coverage setting. However, occupation was associated with 1-year mortality after ICU admission.

• 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.