• 응용통계연구
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• 제34권6호
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• pp.957-968
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• 2021

역중도절단확률가중(inverse censoring probability weighting, ICPW)은 생존분석에서 흔히 사용되는 방법이다. 중도절단 회귀모형과 같은 ICPW 방법의 응용에 있어서 중도절단 확률의 정확한 추정은 핵심적인 요소라고 할 수 있다. 본 논문에서는 중도절단 확률의 추정이 ICPW 기반 중도절단 회귀모형의 성능에 어떠한 영향을 주는지 모의실험을 통하여 알아보았다. 모의실험에서는 Kaplan-Meier 추정량, Cox 비례위험(proportional hazard) 모형 추정량, 그리고 국소 Kaplan-Meier 추정량 세 가지를 비교하였다. 국소 KM 추정량에 대해서는 차원의 저주를 피하기 위해 공변량의 차원축소 방법을 추가적으로 적용하였다. 차원축소 방법으로는 흔히 사용되는 주성분분석(principal component analysis, PCA)과 절단역회귀(sliced inverse regression)방법을 고려하였다. 그 결과 Cox 비례위험 추정량이 평균 및 중위수 중도절단 회귀모형 모두에서 중도절단 확률을 추정하는 데 가장 좋은 성능을 보여주었다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2003년도 춘계학술대회
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• pp.109-119
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• 2003

In this paper we propose a local smoothing of the Nelson type estimator for the survival function based on an approximation by the Weibull distribution function. It appears that Mean Square Error and Bias of the smoothed estimator of the Nelson type survival function estimator is significantly smaller then that of the smoothed estimator of the Kaplan-Meier survival function estimator.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.279-287
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• 2003

In this paper we propose a local smoothing of the Nelson type estimator for the survival function based on an approximation by the Weibull distribution function. It appears that Mean Square Error and Bias of the smoothed estimator of the Nelson type survival function estimators are significantly smaller than that of the smoothed estimator of the Kaplan-Meier survival function estimator.

• 지역사회간호학회지
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• 제32권1호
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• pp.107-115
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• 2021

Purpose: The purpose of this study is to identify factors associated with smoking relapse within six months after quit attempts among workers in small and medium-sized enterprises in South Korea. Methods: The analysis was conducted for a total of 194 people who attempted to quit smoking by applying for a smoking cessation support service at the Regional Tobacco Control Center. The data used in the study were extracted from the Smoking Cessation Service Integrated Information System. Kaplan-Meier estimator and Cox proportional hazards regression model were used to identify variables associated with smoking relapse within six months' time period. Results: Smoking relapse rate within six months was 66.0%, and variables associated with relapse included the cases such as carbon monoxide (CO) at the time of registration (HR: 2.15, 95% CI: 1.10~4.22 for CO ≥20 ppm or more vs.CO <10 ppm), the average number of cigarettes smoked per day (HR: 1.04, 95% CI: 1.00~1.07), and the number of counseling(HR: 0.60, 95% CI: 0.54~0.67). Conclusion: Smoking characteristics and counseling showed one of the strongest correlations with relapse within six months. This implies that it is necessary to understand the smoking characteristics and patterns of workers and to provide continuous smoking cessation counseling tailored to individual characteristics for effective smoking relapse prevention.