• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.39-43
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• 1999

We consider generalized exponential regression model with randomly censored data and propose a modified Fisher scoring method which estimates the model parameters. For this, the likelihood equations are derived and then the estimating algorithm is developed. We illustrate the proposed method using a real data.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.467-475
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• 2015

Accurate demand forecasting is a crucial component in revenue management(RM). The booking data of departed flights is used to forecast the demand for future departing flights; however, some booking requests that were denied were omitted in the departed flights data. Denied booking requests can be interpreted as censored in statistics. Thus, unconstraining demand is an important issue to forecast the true demands of future flights. Several unconstraining methods have been introduced and a method based on expectation maximization is considered superior. In this study, we propose a new unconstraining method based on a regression model that can entertain such censored data. Through a simulation study, the performance of the proposed method was evaluated with two representative unconstraining methods widely used in RM.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.313-322
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• 2007

Several robust censored depth regression methods are compared under contamination. Park and Hwang(2003) suggested a way to circumvent the censoring issue by incorporating Kaplan-Meier type weight in halfspace regression depth and Park(2003) used a similar technique to simplicial regression depth. Hubert et al. (2001) suggested a high breakdown point regression depth based on projection called rcent. A new method to implement censoring in rcent is suggested and compared with two precedents under various contamination and censoring schemes.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.739-748
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• 2012

In this paper we propose a mixed effects least squares support vector machine (LS-SVM) for the censored data which are observed from different groups. We use weights by which the randomly right censoring is taken into account in the nonlinear regression. The weights are formed with Kaplan-Meier estimates of censoring distribution. In the proposed model a random effects term representing inter-group variation is included. Furthermore generalized cross validation function is proposed for the selection of the optimal values of hyper-parameters. Experimental results are then presented which indicate the performance of the proposed LS-SVM by comparing with a standard LS-SVM for the censored data.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.379-393
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• 2020

A terminal event such as death may censor an intermediate event such as relapse, but not vice versa in semi-competing risks data, which is often seen in medicine, public health, and epidemiology. We propose a Weibull regression model with a normal frailty to analyze semi-competing risks data when all three transition times of the illness-death model are possibly interval-censored. We construct the conditional likelihood separately depending on the types of subjects: still alive with or without the intermediate event, dead with or without the intermediate event, and dead with the intermediate event missing. Optimal parameter estimates are obtained from the iterative quasi-Newton algorithm after the marginalization of the full likelihood using the adaptive importance sampling. We illustrate the proposed method with extensive simulation studies and PAQUID (Personnes Agées Quid) data.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.325-333
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• 1999

경북대학교병원에서 1985년에서 1994년까지 위암 때문에 위 절제수술을 받은 1,192명의 환자에 대한 자료를 이용하여 5년 생존율에 관해 분석하고자 한다. 일반적으로 위암 진단을 받은 환자가 수술을 받으려고 할 때 또는 수술을 직후에, 환자의 임상적 특성들을 이용하여 수술후 생존시간과 수술후 5년 생존 여부는 큰 의미가 있다. 그러나 많은 경우에 있어서 실제 임상자료는 연구가 진행 중에 있으므로 생존시간이 우측 중도절단된 형태로 관측되어 기존의 판별분석과 로짓분석을 적용할 수 없다. 본 논문에서는 Buckley와 James가 제안한 의사확률변수를 이용하여 수술전과 수술직후, 두 시점에서 중도절단된 자료를 보완하고, 판별분석과 로짓분석을 통하여 수술전과 수술직후에 환자들의 각 특성이 5년 생존여부에 미치는 영향을 분석을 한다.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.339-348
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• 2021

This paper aims to analyze the production efficiency in Korea's ten service sectors using DEA and its determinants utilizing a truncated-Tobit regression model and a censored-Tobit regression model in 2010-2019. This paper found: First, the Korean service sector's production efficiency in general has been significantly low and polarized. Especially, the inefficiency resulted from the scale inefficiency in the 'sewerage waste management industry.' Second, in the determinants analysis, the results show the positive effect of the investment and R&D expenses on technical efficiency, while FDI and lobbying expenses illustrate the negative impact. Moreover, it seems that the larger the industry, the higher the efficiency. Thus, the future Korean government's economic policy for the service sectors requires a mixed and integrated policy of the macroeconomic aspect such as active investment and R&D activities with microeconomic aspect including a convergence of FDI and human capital.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• Journal of the Korean Data and Information Science Society
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• v.4
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• pp.13-30
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• 1993

We propose the ordered least squares estimators(OLSE's) of the parameters and the p-th quantiles for the two-parameter Weibull regression model under the Type II censoring, The Monte Carlo simulations are performed to compare the proposed estimators with the maximum likelihood estimators(MLE's), and it is shown that the proposed estimators are slightly better than MLE's as the censoring rate goes up.