• 유통과학연구
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• 제15권11호
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• pp.49-57
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• 2017

Purpose - In Korea, general super markets have a great impact on the market performance of traditional markets. We propose a modified two stage DEA model for evaluating the performance of traditional markets in Incheon, Korea by identifying the influence of external environmental factors including the presence of general super markets as non-discretionary variables in DEA. Research design, data, and methodology - After obtaining bias-corrected estimates of original DEA efficiency scores using the input and output data of 49 traditional markets, we regress them on several external environmental factors by bootstrap-truncated regression. Results - We obtain bias-corrected efficiency scores from the original DEA efficiency scores by bootstrap and among the five environmental factors, the residential population and the presence of general super markets or SSMs can be considered as the driving forces influencing bias-corrected efficiency scores, positively and negatively, respectively. Conclusions - When DEA efficiency scores tend to be overestimated, we need to use a biased-corrected efficiency score by bootstrap. It is important to note that the efficiency of traditional markets can be largely influenced by external environmental factors such as the presence of general super markets or SSMs that traditional markets can not control. Therefore, it is desirable to consider such environmental factors appropriately for a reasonable performance evaluation.

• 임상간호연구
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• 제28권1호
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• pp.23-33
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• 2022

Purpose: This study aimed to identify the relationships among disease severity, anxiety, depression, social support, unpleasant symptoms and self-care among patients with atrial fibrillation based on the unpleasant symptom theory, and to examine the mediating effects of unpleasant symptoms. Methods: A cross-sectional study was conducted. The participants were 216 patients with atrial fibrillation who were being followed up on an outpatient basis at a university hospital in Seoul. Data were collected from November 1, 2020 to June 30, 2021, using self-report questionnaires. Data were analyzed using IBM SPSS/WIN 27.0 and PROCESS macro with 95% bias-corrected bootstrap confidence interval(CI). Results: The average age of participants in this study was 66.0years. Disease severity (β=10.19, p<.001) and depression (β=1.53, p<.001) had significant positive relationships with unpleasant symptoms. Also, unpleasant symptoms (β=-0.03, p=.006) had a negative relationship with physical activity, which is a subscale of self- care. Social support (β=0.06, p<.001) was positively related with physical activity. Unpleasant symptoms showed a mediation effect in the relationship between disease severity and physical activity (Bias corrected bootstrap CI -0.65, -0.04). Depression had an indirect effect on physical activity that was mediated by unpleasant symptoms (Bias corrected bootstrap CI -0.11, -0.00). Conclusion: The findings of this study suggest that integrated strategies including physical, psychological, and social factors should be considered to promote self-care in patients with atrial fibrillation.

• 대한수의학회지
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• 제47권2호
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• pp.259-263
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• 2007

The choice of input distribution in quantitative risk assessments modeling is of great importance to get unbiased overall estimates, although it is difficult to characterize them in situations where data available are too sparse or small. The present study is particularly concerned with accommodation of uncertainties commonly encountered in the practice of modeling. The authors applied parametric and non-parametric bootstrap simulation methods which consist of re-sampling with replacement, in together with the classical Student-t statistics based on the normal distribution. The implications of these methods were demonstrated through an empirical analysis of trade volume from the amount of chicken and pork meat imported to Korea during the period of 1998-2005. The results of bootstrap method were comparable to the classical techniques, indicating that bootstrap can be an alternative approach in a specific context of trade volume. We also illustrated on what extent the bias corrected and accelerated non-parametric bootstrap method produces different estimate of interest, as compared by non-parametric bootstrap method.

• Communications for Statistical Applications and Methods
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• 제3권3호
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• pp.291-297
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• 1996

In this paper, we propose the jackknife estimator and the bootstrap estimator of Gini index of the two-parameter exponential distribution when the location parameter $\theta$ is unknown and the scale parameter $\sigma$is known. Sinilarly, we propose the bias location parameter $\theta$ and the scale parameter $\sigma$ are unknown. The bootstrap estimator is more efficient than the other estimators when the location parameter $\theta$is unknown and the scale parameter $\sigma$ is known, and the bias corrected estimator is more efficient than the MLE when both the location parameter $\theta$ and the scale parameter $\sigma$are unknown.

• 수산경영론집
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• 제47권1호
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• pp.63-86
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• 2016

The purpose of this study is to investigate production efficiency of Oceans and Fisheries Human Resources Development Programs Efficiency using Bootstrap-DEA. The study extracts 33 officials curriculum, 11 fisheries managers curriculum for its analytical. First, the study estimates technical, pure technical, and scale efficiency of each curriculums based on traditional DEA under the assumption of CRS and VRS. 8(official 7, managers 1) curriculums are identified as efficient DMUs under the CCR-model, and 13(official 10, managers 3) under the BCC-model. We provide inputs that allow inefficient curriculum to be efficient DMUs on a production frontier, and a reference set for their bench-marking. Second, rank test, Wilcoxon-Mann-Whitney test to find a statistical significance of heterogeneity existing in efficiences between Bootstrap-DEA tenical vs Bootstrap-DEA pure technical was no significant difference. We have identified that G10, 11, 12 13, 25, 31, 33, 39 curriculums are the most efficiently produced in the technical and pure technical efficiency. Also we managed to measure the inefficiency which exists in efficiently produced curriculums when estimating the bias corrected efficiency scores. In Technical efficiency, Operation and facility was significant at the 10%. In Pure technical efficiency, facility was significant at the 10%.

• The Korean Journal of Physiology and Pharmacology
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• 제13권5호
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• pp.367-371
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• 2009

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled data sets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.

• Communications for Statistical Applications and Methods
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• 제6권2호
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• pp.621-634
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• 1999

Consider the several methods of constructing interval for relative ration from two independent binomial samples. The special interests are gives in the cases of low rates and small samples. bias-corrected and accelerated bootstrap method is proposed to overcome are the non-efficiency of current methods based on asymptotic resuts. Simulation studies are presented to demonstrate the performance of the proposed method.

• 한국콘텐츠학회논문지
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• 제15권5호
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• pp.475-487
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• 2015

본 연구에서는 부트스트랩 DEA를 이용하여 2013년 14개 공기업의 경영 효율성을 분석하였다. 또한 단절회귀분석을 이용하여 부트스트랩 편의조정 효율성에 영향을 미치는 요인을 분석하였다. 본 연구를 통해 도출된 결과와 시사점을 정리하면 다음과 같다. 첫째, 부트스트랩 DEA모형을 적용한 효율성 분석결과에 따르면 평균 기술효율성이 0.3182, 평균 순수기술효율성이 0.4994, 평균 규모효율성이 0.6585로 나타났으며, 기술비효율성의 주된 원인이 순수기술비효율성에 기인하는 것으로 분석되었다. 둘째, CRS 가정과 VRS 가정하의 일반 DEA모형을 적용한 TE와 부트스트랩 DEA모형을 적용한 TE 순위간에는 유의한 차이가 없는 것으로 나타났다. 셋째, 비효율원인 분석에서는 평가대상 14개 기관 중 11개 기관의 비효율원인이 순수기술에 더 크게 기인하고 있고, 3개 기관이 규모효율에 의해 비효율이 나타나는 것으로 분석되었다. 넷째, 단절회귀분석에서는 규모효율성에 영향을 미치는 요인으로 유의수준 10%에서 인건비, 영업이익, 매출액, 자기자본수익률, 종원원수 순으로 나타났다.

• 응용통계연구
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• 제19권1호
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• pp.1-12
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• 2006

본 논문에서는 2002년에 (사)볼런티어21에서 실시한 설문조사 자료를 이용하여 2001년에 우리나라 개인들이 기부한 횟수에 영향을 주는 유의한 변수들을 식별하였다. 기부횟수의 경험적 분포로 미루어 모집단은 기부를 적게 하는 집단과 많이 하는 집단으로 구성되며 따라서 모집단 분포를 두개 포아송 분포의 혼합분포로 모형화하였다. 이 모형에 기초하여 기부횟수에 영향을 미치는 변수들을 식별하였다. EM알고리즘을 이용하여 모수를 추정하고 2.5%와 97.5%에 기초한 백분위수 신뢰구간을 보완한 BCa(bias-corrected and accelerated) 신뢰구간을 계산하여 유의한 변수들을 찾았다. 연구결과 혼합 포아송 회귀모형에서는 기부횟수가 적은 집단("작은 군")과 기부횟수가 많은 집단("큰 군") 모두에서 소득과 자원봉사의 경험 유무(1:예, 0:아니오)가 기부횟수에 유의적으로 영향을 주는 변수로 밝혀졌다. 또한 두 변수 각각에서 회귀계수가 양수로 나타나 소득이 많을수록, 혹은 자원봉사의 경험이 있는 사람일수록 기부횟수가 증가하는 것을 알 수 있다. 그러나 소득과 자원봉사 변수의 회귀계수는 "작은 군"이 "큰 군"에 비해 더욱 크게 나타나고 있다. "작은 군"보다 "큰 군"의 사람들에게 기부가 생활화되어 있고, 따라서 소득과 자원봉사의 경험 유무가 기부횟수에 미치는 영향이 상대적으로 적은 것으로 파악된다.

• 대한간호학회지
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• 제50권5호
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• pp.728-736
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• 2020

Purpose: This study aimed to identify the relationship between workplace violence and turnover intention, and the mediation effect of resilience on the relationship in hospital nurses. Methods: This was a cross-sectional study. A total of 237 registered nurses were recruited from three hospitals in South Korea from April to May 2019. Participants were invited to complete self-reported questionnaires that measure workplace violence, turnover intention, resilience, and demographic information. The data obtained were analyzed using multiple regression and a simple mediation model applying the PROCESS macro with 95% bias-corrected bootstrap confidence interval (5,000 bootstrap resampling). Results: After controlling demographic covariates, workplace violence significantly accounted for the variance of turnover intention. It was also demonstrated that resilience partially mediated the relationship between workplace violence and turnover intention in hospital nurses. A 73.8% of nurses had experienced workplace violence (such as attack on personality, attack on professional status, isolation from work, or direct attack). Conclusion: Workplace violence directly influences turnover intention of nurses and indirectly influences it through resilience. Therefore, hospital administrators need to develop and provide a workplace violence preventive program and resilience enhancement program to decrease nurses' turnover intention, and leaving.