• 응용통계연구
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• 제7권2호
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• pp.53-77
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• 1994

병원의 임상연구실험에서 종종 환자들의 치료에 따른 병세의 호전상태를 여러단계로 분류하여 상이한 치료방법에 따른 치료효과간의 차이를 알고자 하는 경우가 있다. 이와 같이 다중상태의 생존자료분석을 위한 한가지 방법으로 본 논문에서는 비동형의 Markov 모형에 Cox 회귀모형을 적용하여 회귀계수와 기저생존함수, 그리고 이를 바탕으로 반응확률함수를 추정하고 아울러 이들 추정량들의 대표본 성질들을 셈과정(Counting process) 기법을 이용하여 알아 보았다. 그리고 본 논문의 결과에 대해 실제 예를 들어 보였다.

• Journal of the Korean Data and Information Science Society
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• 제4권
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• pp.1-11
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• 1993

The Cox's regression model is frequently used for covariate effects in survival data analysis, But, much of the statistical work has focused on asymptotic behavior so the small sample evaluation has been neglected. In this paper, we compare the small or moderate sample performances of the survival function estimators for the Cox's regression model using bootstrap method. The smoothed PL type estimator and the Link estimator are slightly better than corresponding the PL type estimator and the Nelson type estimator in the sense of the achieved error rates.

• 응용통계연구
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• 제21권2호
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• pp.327-340
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• 2008

본 연구에서는 오차항이 AR(1)을 따르는 회귀모형에서 올바른 추론을 도출하고자 모형식별의 문제를 다루었다. 이를 위해 Box-Cox 변환된 회귀모형을 고려하여 (i) Box-Cox 변환모형과 AR(1) 오차에 대한 동시 검정, (ii) AR(1) 오차가 존재하는 모형에서의 Box-Cox 변환모형에 대한 검정 그리고 (iii) 모형이 Box-Cox 변환되어 있을 때 오차가 AR(1) 과정을 따르는지에 대한 LM 검정통계량을 유도하였다. 특히 LM 검정방법에서 여러개의 모수가 비선형관계를 형성하고있어 정보행렬의 추정은 계산상 매우 어렵다. 따라서 정보행렬의 원소에 대한 기대값을 구함에 있어 Taylor전개를 이용하여 정보행렬을 구하고 이에 기반을 둔 LM 검정통계량($LM_E$)를 제안하고 모의실험결과 $LM_E$가 기존의 헤시안행렬에 기반을 둔 LM 검정통계량($LM_H$)에 비하여 유의수준을 잘 유지하고 있는 것으로 나타났다.

• Advances in pediatric surgery
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• 제12권2호
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• pp.202-212
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• 2006

The prognostic factors for extrahepatic biliary atresia (EHBA) after Kasai portoenterostomy include the patient's age at portoenterostomy (age), size of bile duct in theporta hepatis (size), clearance of jaundice after operation (clearance) and the surgeon's experience. The aim of this study is to examine the most significant prognostic factor of EHBA after Kasai portoenterostomy. This retrospective study was done in 51 cases of EHBA that received Kasai portoenterostomy by one pediatric surgeon. For the statistical analysis, Kaplan-Meier method, Logrank test and Cox regression test were used. A p value of less than 0.05 was considered to be significant. Fifteen patients were regarded as dead in this study, including nine cases of liver transplantation. There was no significant difference of survival to age. The age is also not a significant risk factor for survival in this study (Cox Regression test; p = 0.63). There was no significant difference in survival in relation to the size of bile duct. However, bile duct size was a significant risk factor for survival (Cox Regression test; p = 0.002). There was a significant difference in relation to survival and clearance (Kaplan-Meier method; p = 0.02). The clearing was also a significant risk factor for survival (Cox Regression test; p = 0.001). The clearance of jaundice is the most significant prognostic factor of EHBA after Kasai portoenterostomy.

• Asian Pacific Journal of Cancer Prevention
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• 제16권15호
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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.

• 응용통계연구
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• 제15권2호
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• pp.233-250
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• 2002

Cox의 비례위험모형(proportional hazards model)은 생존자료(survival data)에 대한 회귀모형으로 경제학 및 의·공학을 비롯한 여러 응용 분야에서 가장 널리 쓰이고 있는 모형 중 하나이다. 그러나, 이 모형은 일반선헝모형에 비해 잔차 분석을 통한 회귀 진단의 연구가 널리 알려져 있지 않아, 국내의 실제 자료 분석에서는 잔차 분석에 대한 활용이 거의 이루어지지 않고 있는 실정이다. 이에 본 논문에서는 그 동안 제안된 여러 잔차들을 비교 분석하고, S-plus 프로그램을 이용한 PBC(primary biliary cirrhosis) 자료분석을 통해 각 잔차들의 의미를 고찰하고자 한다.

• 대한가정학회지
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• 제42권1호
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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.

• Communications for Statistical Applications and Methods
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• 제24권2호
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• pp.115-127
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• 2017

This paper proposes a Bayesian test for the equivalence of survival functions in multiple groups. Proposed Bayesian test use the model of Cox's regression with time-varying coefficients. B-spline expansions are used for the time-varying coefficients, and the proposed test use only the partial likelihood, which provides easier computations. Various simulations of the proposed test and typical tests such as log-rank and Fleming and Harrington tests were conducted. This result shows that the proposed test is consistent as data size increase. Specifically, the power of the proposed test is high despite the existence of crossing hazards. The proposed test is based on a Bayesian approach, which is more flexible when used in multiple tests. The proposed test can therefore perform various tests simultaneously. Real data analysis of Larynx Cancer Data was conducted to assess applicability.

• Journal of the Korean Wood Science and Technology
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• 제12권3호
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• pp.3-8
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• 1984

섬유의 방향성이 무질서한 composites에 적용되는 Smith와 Cox의 이론(理論)을 포함한 Paul과 Jones의 혼합이론식(混合理論式)은 유황(硫黃) 화합물(化合物)을 사용하여 제조한 목재섬유 복합재(複合材)에도 일차적(一次的)인 liner regression constant가 주어질 때는 사용할 수가 있음을 보여준다. $E_c=\frac{1}{3}aE_fV_f+bE_mV_m$으로 표시된 이 liner regression from에 math. rom pack을 사용한 Hewlett Packard 75C(HP 75C) computer의 계산 결과는 목재 섬유 복합재(複合材)에 사용된 matrix의 종류, 섬유판의 밀도와 목재 밑 목질 섬유의 종류에 관계없이 a=3.27~3.54와 b=-2.47~-2.80의 일정한 범위의 값을 보여주므로, 지금까지 무(無)질서한 방향성을 지닌 장(長)섬유로 된 복합재(複合材)에만 적용되어 왔던 Paul과 Jones의 혼합이론(混合理論)과 이것과 같은 방향을 지닌 단(短) 섬유로 된 목재(木材)나 목질(木質) 섬유 composites에도 적용될 수 있음을 증명하고 있다.

• Journal of the Korean Data and Information Science Society
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• 제28권5호
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• pp.1191-1204
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• 2017

Weighted least squares (WLS) estimation is often easily used for the data with heteroscedastic errors because it is intuitive and computationally inexpensive. However, WLS estimator is less robust to a few outliers and sometimes it may be inefficient. In order to overcome robustness problems, Box-Cox transformation, Huber's M estimation, bisquare estimation, and Yohai's MM estimation have been proposed. Also, more efficient estimations than WLS have been suggested such as Bayesian methods (Cepeda and Achcar, 2009) and semiparametric methods (Kim and Ma, 2012) in heteroscedastic error models. Recently, Çelik (2015) proposed the weight methods applicable to the heteroscedasticity patterns including butterfly-distributed residuals and megaphone-shaped residuals. In this paper, we review heteroscedastic regression estimators related to robust or efficient estimation and describe their properties. Also, we analyze cost data of U.S. Electricity Producers in 1955 using the methods discussed in the paper.