• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.583-604
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• 2017

The most popular regression model for the analysis of time-to-event data is the Cox proportional hazards model. While the model specifies a parametric relationship between the hazard function and the predictor variables, there is no specification regarding the form of the baseline hazard function. A critical assumption of the Cox model, however, is the proportional hazards assumption: when the predictor variables do not vary over time, the hazard ratio comparing any two observations is constant with respect to time. Therefore, to perform credible estimation and inference, one must first assess whether the proportional hazards assumption is reasonable. As with other regression techniques, it is also essential to examine whether appropriate functional forms of the predictor variables have been used, and whether there are any outlying or influential observations. This article reviews diagnostic methods for assessing goodness-of-fit for the Cox proportional hazards model. We illustrate these methods with a case-study using available R functions, and provide complete R code for a simulated example as a supplement.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.957-968
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• 2021

Inverse censoring probability weighting (ICPW) is a popular technique in survival data analysis. In applications of the ICPW technique such as the censored regression, it is crucial to accurately estimate the censoring probability. A simulation study is undertaken in this article to see how censoring probability estimate influences model performance in censored regression using the ICPW scheme. We compare three censoring probability estimators, including Kaplan-Meier (KM) estimator, Cox proportional hazard model estimator, and local KM estimator. For the local KM estimator, we propose to reduce the predictor dimension to avoid the curse of dimensionality and consider two popular dimension reduction tools: principal component analysis and sliced inverse regression. Finally, we found that the Cox proportional hazard model estimator shows the best performance as a censoring probability estimator in both mean and median censored regressions.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6773-6777
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• 2015

We used to LASSO-Cox method for determining prognostic factors of male breast cancer survival and showed the superiority of this method compared to Cox proportional hazard model in low sample size setting. In order to identify and estimate exactly the relative hazard of the most important factors effective for the survival duration of male breast cancer, the LASSO-Cox method has been used. Our data includes the information of male breast cancer patients in Fars province, south of Iran, from 1989 to 2008. Cox proportional hazard and LASSO-Cox models were fitted for 20 classified variables. To reduce the impact of missing data, the multiple imputation method was used 20 times through the Markov chain Mont Carlo method and the results were combined with Rubin's rules. In 50 patients, the age at diagnosis was 59.6 (SD=12.8) years with a minimum of 34 and maximum of 84 years and the mean of survival time was 62 months. Three, 5 and 10 year survival were 92%, 77% and 26%, respectively. Using the LASSO-Cox method led to eliminating 8 low effect variables and also decreased the standard error by 2.5 to 7 times. The relative efficiency of LASSO-Cox method compared with the Cox proportional hazard method was calculated as 22.39. The19 years follow of male breast cancer patients show that the age, having a history of alcohol use, nipple discharge, laterality, histological grade and duration of symptoms were the most important variables that have played an effective role in the patient's survival. In such situations, estimating the coefficients by LASSO-Cox method will be more efficient than the Cox's proportional hazard method.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.723-736
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• 2013

The importance of lapse rate is highly increasing due to the introduction of Cash Flow Pricing system, non-refund-of-reserve insurance policy, and IFRS (International Financial Reporting System) to the Korean insurance market. Researches on lapse rate have mainly focused on simple data analysis and regression analysis, etc. However, lapse rate can be analyzed by survival analysis and can be well explained in terms of several covariates with Cox proportional hazard model. Guaranteed minimum benefits embedded in variable annuities require more elegant statistical analysis of lapse rate. Hence, this paper analyzes data of policyholders with variable annuities by using Cox proportional hazard model. The key variables of policy holder that influences the lapse rate are payment method, premium, lapse insured to term insured, reserve-GMXB ratio, and age.

• Journal of Chest Surgery
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• v.42 no.6
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• pp.710-718
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• 2009

Background: The Cox maze procedure has been used as a standard surgical treatment for atrial fibrillation for about 20 years. Recently, the creators have used a bipolar radiofrequency electrode (Cox maze IV procedure) instead of the incision and suture (cut-sew) technique to make atrial ablation lesions for persistent atrial fibrillation. We investigated clinical outcomes for the Cox maze procedure with a bipolar radiofrequency electrode and cryoablator in patients with persistent atrial fibrillation, and compared results with clinical outcomes of the cut-sew procedure. Material and Method: Between April 2005 and July 2007, 40 patients with persistent atrial fibrillation underwent Cox maze IV procedure with a bipolar radiofrequency electrode and cryoablator (bipolar radiofrequency group). Surgical outcomes were compared with those of 35 patients who had the cut-sew technique for the Cox maze III procedure. All patients had concomitant cardiac surgery. Postoperatively, the patients were followed up every 1 to 2 months. Result: At 6 months postoperatively, the conversion rate to regular sinus rhythm was not significantly different between the two groups: 95.0% for the bipolar radiofrequency ablation group; 97.1% for the cut-sew technique (p=1.0). At the end of the follow-up period, the conversion rate to regular sinus rhythm was also not significantly different (92.5% vs. 91.6%, p=1.0). In multivariate analysis using a Cox-regression model, the postoperative atrial dimension was an independent determinant of sinus conversion in the bipolar radiofrequency ablation group (hazard ratio 31, p=0.005). In the Cox-regression model for both groups, atrial fibrillation at 6 months postoperatively (hazard ratio 92.24, p=0.003) and the postoperative left atrial dimension (hazard ratio 16.05, p=0.019) were independent risk factors of continuance or recurrence of atrial fibrillation after Cox maze procedures. Aortic cross-clamp time and cardiopulmonary bypass time were significantly shorter in the radiofrequency group than in the cut-sew group. Conclusion: In the Cox maze procedure for patients with persistent atrial fibrillation, the use of bipolar radiofrequency ablation and a cryoablator is as good as the cut-sew technique for conversion to sinus rhythm. The postoperative left atrial dimension is an independent determinant of postoperative continuance and recurrence of atrial fibrillation.

• Journal of the Korean Home Economics Association
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• v.42 no.1
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• pp.69-79
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• 2004

This study has examined factors of young married women's new entry in labor market after the birth of their first child. For the dynamic analysis, the Cox Regression Hazard Model is applied. The following results are obtained： First, about 33％ of married women who did not have a job at the pre-birth enter in labor market at the post-birth. Second, compared to those out of the labor force, women who succeeded in finding their first jobs after the birth of their first child are more likely to be younger, have baby-sitters, have working experiences in the past, and have lower level of household income. Third, age, having baby-sitter and the experience of job transition are vital factors in entering the labor market after the first child birth.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.233-250
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• 2002

Cox's proportional hazard model is highly-used for the regression analysis of survival data in various fields. Regression diagnostics for the proportional hazards model, however, is not as well-known as the diagnostics for the classical linear models and so these diagnostic methods are not used widely in our practical data analyses. For this reason, we review the residuals proposed by several authors, and investigate how to use them in assessing the model. We also provide the results and interpretation with the analysis of PBC data using S-plus 2000 program.

• 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.

• 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.