• Journal of Korean Academy of Nursing
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• v.42 no.6
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• pp.819-832
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• 2012

Purpose: This study was conducted to identify risk factors that influence the probability and severity of elder abuse in community-dwelling older adults. Methods: This study was a cross-sectional descriptive study. Self-report questionnaires were used to collect data from community-dwelling Koreans, 65 and older (N=416). Logistic regression, negative binomial regression and zero-inflated negative binomial regression model for abuse count data were utilized to determine risk factors for elder abuse. Results: The rate of older adults who experienced any one category of abuse was 32.5%. By zero-inflated negative binomial regression analysis, the experience of verbal-psychological abuse was associated with marital status and family support, while the experience of physical abuse was associated with self-esteem, perceived economic stress and family support. Family support was found to be a salient risk factor of probability of abuse in both verbal-psychological and physical abuse. Self-esteem was found to be a salient risk factor of probability and severity of abuse in physical abuse alone. Conclusion: The findings suggest that tailored prevention and intervention considering both types of elder abuse and target populations might be beneficial for preventative efficiency of elder abuse.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.887-894
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• 2018

An electric vehicle is emerging as an alternative to the response of global climate change and sustainability. However, an Electric vehicle has not been popular due to the constraints such as its price or technical limitations. In order to analyze the effect of purchasing electric vehicles, this study conducted a binary logistic regression model that demonstrates the relation between purchasing and influencing variables. Variables which have high correlation were excluded from the model through the correlation analysis to prevent multicollinearity. Socio-economic variables such as the number of owned vehicles, sex, ages are not significant. On the other hand, Variables related to prices, charging and policy are found to have a significant to effect on the purchase of electric vehicles. In accordance with the model estimated result, it seems to be necessary to improve the charging incentives, or to provide electric car information and to expand opportunities for experience electric vehicles. The result is also expected to be helpful for spreading electric vehicles and formulating policies.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7923-7927
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• 2015

Background: The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. Materials and Methods: In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. Results: The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Conclusions: Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.445-459
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• 2014

As a certain job is repeatedly done by a worker, the outcome comparative to the effort to complete the job gets more remarkable. The outcome may be the time required and fraction defective. This phenomenon is referred to a learning-curve effect. We focus on the parametric modeling of the learning-curve effects on count data using a logistic cumulative distribution function and some probability mass functions such as a Poisson and negative binomial. We conduct various simulation scenarios to clarify the characteristics of the proposed model. We also consider a real application to compare the two discrete-type distribution functions.

• Journal of the Korean Home Economics Association
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• v.48 no.2
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• pp.135-144
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• 2010

This study explores whether or not marriage and other family values operate as factors that influence the willingness of women to voluntarily remain ever-single. The study includes as variables the sub-fields of marriage and family values that consist of traditional gender role awareness, freedom in sexual attitude, open outlook on marriage, familism, an acceptance of diverse families, fear of marriage, and assignment of value to extramarital factors. Participants of this study were 259 women in their twenties to forties with no experience of marriage, which were selected from the data used in the Korean Women's Development Institute's Investigation of Single Households(2007). Upon inserting value-related variables and sociodemographic variables into a binomial logistic model for analysis, age, open outlook on marriage, assigned value on extramarital factors, and an acceptance of diverse families were shown to be factors influencing the willingness of women to remain ever-single. That is, as the age spectrum is lower, outlook on marriage is open, more values are granted on the extramarital factors, and the degree of an acceptance of diverse views on family is higher, the chances that women would remain ever-single voluntarily were shown to increase.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.9-20
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• 2005

Accident type and/or factor identification is important in accident reduction planning. The aim of this paper is to apply the hierarchical approach with binomial distribution and logistic regression analysis to find out types and factors, respectively. Based on 2001 Suwon city black spot data, a binomial distribution modeling approach has been applied to diagnose the black spots, with the help of safety performance modeling approach has been applied to diagnose the black spots, with the help of safety performance function. Then, the logistic regression analysis has been employed to identify the critical factors. Some accident remedies are also reviewed in the light of the model outcomes. The proposed research framework sheds light on a different accident related research and can also be successfully applied to similar studies and sites.

• Journal of Navigation and Port Research
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• v.42 no.5
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• pp.341-346
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• 2018

Supramax bulk carriers cover a wide range of ocean transportation requirements, from major to minor bulk cargoes. Market forecasting for this segment has posed a challenge to researchers, due to complexity involved, on the demand side of the forecasting model. This paper addresses this issue by using technical indicators as input features, instead of complicated supply-demand variables. Artificial neural networks (ANN), one of the most popular machine-learning tools, were used to replace classical time-series models. Results revealed that ANN outperformed the benchmark binomial logistic regression model, and predicted direction of the spot market with more than 70% accuracy. Results obtained in this paper, can enable chartering desks to make better short-term chartering decisions.

• Korean Journal of Organic Agriculture
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• v.21 no.4
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• pp.555-567
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• 2013

The objective of this study is to analyze the willingness to change into organic blueberry and the activating strategies on domestic products. For the activation of domestic blueberry, it is necessary to get the quality certification, especially organic certificate and develop the technology for increasing production. It is investigated that the smaller product, younger farmer and higher price expected, the higher willingness to change into organic blueberry. The results and finding of this study can be used to build-up the technical and marketing supporting system that reflects the rapid change of customer's preference on blueberry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.253-268
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• 2020

This study examined the effectiveness of policy measures in a growth management plan by analyzing empirically the influence of regulations and incentives in a non-urban growth management plan of Sejong City using the binomial logistic model. The parcel unit data related development location of Sejong City from 2012 to 2017 was used in the model. The analysis showed that time regulation in the growth management plan has a negative (-) impact on the spread of development, which means it is effective in slowing urban sprawl by lowering the profits of developers. The time regulation applied in Sejong City needs to be used actively in other cities in Korea to prevent urban sprawl. Nevertheless, floor ratio incentives had no influence in inducing development within the growth management area, which means a new incentive policy to meet the local characteristics is needed to strengthen the effectiveness of the growth management plan. This study is meaningful because it attempted an empirical analysis of the effects of the growth management plan at The National Territory Act, and this study could encourage further studies.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1349-1364
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• 2006

An analytic approach that provides explicit estimates of risk on cataract and epilation data is evaluated by reasonableness of conceivable relative risk models regarding a simple, odds, logistic or Gompertz regression method, assuming a binomial distribution. In these analyses, we apply relative risk models with two thresholds between epilators and nonepilators from a highly characteristic lesion of which radiation cataract does not occur around 2 gray for a single acute exposure. The risk models are fitted to the data assuming 10 as a constant relative biological effectiveness of neutron. The likelihood of observing the entire data set in these models fitted is evaluated by an individual binary-response array. Estimation of a threshold with or without severe epilation and the 100 ($1-\alpha$)% confidence limits are derived from the maximum likelihood approach. The relative risk model with two thresholds can be expressed as a formula with structure of Background $\times$ RR, where RR includes threshold models with or without epilation. The radiosensitivity of ionizing radiation to cataracts has been examined for the relationship between epilators and nonepilators.