• Journal of Preventive Medicine and Public Health
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• 제48권4호
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• pp.216-224
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• 2015

Objectives: Decreased fertility and impaired health owing to early menopause are significant health issues. Smoking is a modifiable health-related behavior that influences menopausal age. We investigated the effects of smoking-associated characteristics on menopausal age in Korean women. Methods: This study used data from the Korea National Health and Nutrition Examination Survey from 2007 to 2012. Menopausal age in relation to smoking was analyzed as a Kaplan-Meier survival curve for 11 510 women (aged 30 to 65 years). The risk of entering menopause and experiencing early menopause (before age 48) related to smoking were assessed using a Cox proportional hazards model. Results: The menopausal age among smokers was 0.75 years lower than that among non-smokers (p<0.001). The results of the Cox proportional hazards model showed pre-correction and post-correction risk ratios for entering menopause related to smoking of 1.26 (95% confidence interval [CI], 1.09 to 1.46) and 1.27 (95% CI, 1.10 to 1.47), respectively, and pre-correction and post-correction risk ratios for experiencing early menopause related to smoking of 1.36 (95% CI, 1.03 to 1.80) and 1.40 (95% CI, 1.05 to 1.85), respectively. Conclusions: Smokers reached menopause earlier than non-smokers, and their risk for experiencing early menopause was higher.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 추계 학술발표회 논문집
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• pp.197-201
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• 2002

The healthy worker effect is an important issue in occupational epidemiology. We proposed a new statistical method to test the relationship between exposure and time to death in the presence of the healthy worker effect. In this study, we considered the healthy worker hire effect to operate as a confounder and the healthy worker survival effect to operate as a confounder and an intermediate variable. The basic idea of the proposed method reflects the length bias-sampling caused by changing one's employment status. Simulation studies were also carried out to compare the proposed method with the Cox proportional hazards models. According to our simulation studies, both the proposed test and the test based on the Cox model having the change of the employment status as a time-dependent covariate seem to be satisfactory at an upper 5% significance level. The Cox models, however, are inadequate with the change, if any, of the employment status as time-independent covariate. The proposed test is superior in power to the test based on the Cox model including the time-dependent employment status.

• 응용통계연구
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• 제28권2호
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• pp.309-324
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• 2015

본 논문에서는 SRC-Stat 통계패키지를 이용하여 생존자료를 분석하는 방법을 소개한다. 본 패키지는 단변량 생존 자료 분석을 위한 콕스의 비례위험모형 뿐만아니라, 다변량 생존자료분석을 위한 공통 및 지분 프레일티 모형과 같은 고급 생존분석법을 제공한다. 잘 알려져 있는 실제자료의 사용을 통해 본 패키지의 유용성을 예증한다.

• Asian Pacific Journal of Cancer Prevention
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• 제14권4호
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• pp.2477-2481
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• 2013

Aims and Background: The purpose of the research was to study the prognostic value of tumor 18F-FDG PET-based parameters in neoadjuvant chemoradiation for patients with squamous esophageal carcinoma. Methods: Sixty patients received chemoradiation therapy followed by esophagectomy and two 18FDG-PET examinations at pre- and post-radiation therapy. PET-based metabolic-response parameters were calculated based on histopathologic response. Linear regression correlation and Cox proportional hazards models were used to determine prognostic value of all PET-based parameters with reference to overall survival. Results: Sensitivity (88.2%) and specificity (86.5%) of a percentage decrease of SUVmax were better than other PET-based parameters for prediction of histopathologic response. Only percentage decrease of SUVmax and tumor length correlated with overall survival time (linear regression coefficient ${\beta}$: 0.704 and 0.684, P<0.05). The Cox proportional hazards model indicated higher hazard ratio (HR=0.897, P=0.002) with decrease of SUVmax compared with decrease of tumor size (HR=0.813, P=0.009). Conclusion: Decrease of SUVmax and tumor size are significant prognostic factors in chemoradiation of esophageal carcinoma.

• Journal of Preventive Medicine and Public Health
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• 제43권4호
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• pp.330-340
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• 2010

Objectives: This study aims to evaluate and explain the socioeconomic inequalities of all-cause mortality after breast cancer surgery in South Korea. Methods: This population based study included all 8868 females who underwent radical mastectomy for breast cancer between January 2002 and June 2003. Follow-up for mortality continued from January 2002 to June 2006. The patients were divided into 4 socioeconomic classes according to their socioeconomic status as defined by the National Health Insurance contribution rate. The relationship between socioeconomic status and all-cause mortality after breast cancer surgery was assessed using the Cox proportional hazards model with adjusting for age, the Charlson’s index score, emergency hospitalization, the type of hospital and the hospital ownership. Results: Those in the lowest socioeconomic status group had a significantly higher hazard ratio of 2.09 (95% CI =1.50 - 2.91) compared with those in the highest socioeconomic group after controlling for all the identifiable confounding variables. For allcause mortality after radical mastectomy, all the other income groups showed significantly higher 3-year mortality rates than did the highest income group. Conclusions: The socioeconomic status of breast cancer patients should be considered as an independent prognostic factor that affects all-cause mortality after radical mastectomy, and this is possibly due to a delayed diagnosis, limited access or minimal treatment leading to higher mortality. This study may provide tangible support to intensify surveillance and treatment for breast cancer among low socioeconomic class women.

• Communications for Statistical Applications and Methods
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• 제25권5호
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• pp.471-488
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• 2018

In this paper, we propose extending proportional hazards frailty models to allow a discrete distribution for the frailty variable. Having zero frailty can be interpreted as being immune or cured. Thus, we develop a new survival model induced by discrete frailty with zero-inflated power series distribution, which can account for overdispersion. This proposal also allows for a realistic description of non-risk individuals, since individuals cured due to intrinsic factors (immunes) are modeled by a deterministic fraction of zero-risk while those cured due to an intervention are modeled by a random fraction. We put the proposed model in a Bayesian framework and use a Markov chain Monte Carlo algorithm for the computation of posterior distribution. A simulation study is conducted to assess the proposed model and the computation algorithm. We also discuss model selection based on pseudo-Bayes factors as well as developing case influence diagnostics for the joint posterior distribution through ${\psi}-divergence$ measures. The motivating cutaneous melanoma data is analyzed for illustration purposes.

• Journal of the Korean Statistical Society
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• 제26권2호
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• pp.277-288
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• 1997

For the analysis of survival data including covariates whose effects vary in time, the multiprocess discount survival model is proposed. The parameter vector modeling the time-varying effects of covariates is to vary between time intervals and its evolution between time intervals depends on the perturbation of the next time interval. The recursive estimation of the parameter vector can be obtained at the end of each time interval. The retrospective estimation of the survival function and the forecasting of the survival function of individuals of the specific covariates also can be obtained based on the information gathered until the end of the time interval.

• 한국안전학회지
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• 제18권3호
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• pp.54-59
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• 2003

The discharge energy by electrostatic discharge of the charged human body is calculated under the assumption that the stored charge is dissipated completely. However, it is well-known that the charge is slightly remained after electrostatic discharge. Therefore, The Rompe-Weisel model of the discharge analysis, which has somewhat more of a physical justification than the conventional energy equation, is proposed. It is proposed that the electrical conductivity of the arc should be proportional to the energy density transferred to it by Ohmic dissipation. For the electrostatic discharge energy analysis, the Rompe-Weisel model was compared by quasi static analysis. As a consequence, a study on a reliable energy evaluation based on simulation models during electrostatic discharge is carried out in this paper and is adopted to estimate the explosion hazards of flammable gases.

• Journal of Preventive Medicine and Public Health
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• 제40권2호
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• pp.108-113
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• 2007

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

• Communications for Statistical Applications and Methods
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• 제25권6호
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• pp.591-604
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• 2018

The accelerated failure time (AFT) model is a linear model under the log-transformation of survival time that has been introduced as a useful alternative to the proportional hazards (PH) model. In this paper we propose variable-selection procedures of fixed effects in a parametric AFT model using penalized likelihood approaches. We use three popular penalty functions, least absolute shrinkage and selection operator (LASSO), adaptive LASSO and smoothly clipped absolute deviation (SCAD). With these procedures we can select important variables and estimate the fixed effects at the same time. The performance of the proposed method is evaluated using simulation studies, including the investigation of impact of misspecifying the assumed distribution. The proposed method is illustrated with a primary biliary cirrhosis (PBC) data set.