• Research in Community and Public Health Nursing
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• v.13 no.3
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• pp.523-531
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• 2002

Purpose: The purpose of this study was to assess the importance and sensitivity to nursing interventions of six sensitive nursing outcomes selected from the Nursing Outcomes Classification. The outcomes in this study were Self-Care: Activities of Daily Living, Self-Care: Instrumental Activities of Daily Living, Treatment Behavior: Illness or Injury, Knowledge: Health Promotion, Caregiver Performance: Direct Care, and Caregiver Physical Health. Method: Data were collected from 97 visiting nurses working in public health centers located in a province and a capital city. The Fehring method was used to estimate outcomes and indicators for content validity. Simultaneous multiple regression and stepwise regression were used to evaluate relationships between each outcome and its indicators. Results: Results confirmed the importance and nursing sensitivity of the outcomes and their indicators. Multiple regression revealed key indicators of each outcome. Self-Care: Instrumental Activity of Daily Living needed to be revised. Neither all of the indicators nor the indicators showing the highest importance and contribution ratio were selected as independent variables for the stepwise regression model. The R2 of the regression models ranged from 29 to 56% in importance by selected indicators and from 56 to 83% in contribution. Conclusion: Further research is needed for the revision of outcomes and their indicators.

• Journal of Navigation and Port Research
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• v.44 no.3
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• pp.187-194
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• 2020

It is very important to forecast freight volume accurately to establish major port policies and future operation plans. Thus, related studies are being conducted because of this importance. In this paper, stepwise regression analysis and artificial neural network model were analyzed to compare the predictive power of each model on Gwangyang Port, the largest domestic port for coal and iron ore transportation. Data of a total of 121 months J anuary 2009-J anuary 2019 were used. Factors affecting coal and iron ore trade volume were selected and classified into supply-related factors and market/economy-related factors. In the stepwise regression analysis, the tonnage of ships entering the port, coal price, and dollar exchange rate were selected as the final variables in case of the Gwangyang Port coal volume forecasting model. In the iron ore volume forecasting model, the tonnage of ships entering the port and the price of iron ore were selected as the final variables. In the analysis using the artificial neural network model, trial-and-error method that various Hyper-parameters affecting the performance of the model were selected to identify the most optimal model used. The analysis results showed that the artificial neural network model had better predictive performance than the stepwise regression analysis. The model which showed the most excellent performance was the Gwangyang Port Coal Volume Forecasting Artificial Neural Network Model. In comparing forecasted values by various predictive models and actually measured values, the artificial neural network model showed closer values to the actual highest point and the lowest point than the stepwise regression analysis.

• The Journal of the Korea Contents Association
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• v.14 no.2
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• pp.319-329
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• 2014

Purpose: The purpose of this study was to investigate the effect of adolescent's family function, impulsive behavior, stress on the bullying types. Method: Data were collected from 627 adolescents and analyzed using descriptive statistics, t-test, Pearson correlation coefficients and stepwise multiple regression with the SPSS 18.0. Results: The bullying types (injurer and victim) correlates with family function, impulsive behavior and stress. Stepwise multiple regression analysis showed emotional reactivity, non-planning impulsiveness, friends related stress, experience of drinking (yes), experience of parent depression problem (yes), explained 34.1% of the total variance in bully injurer. Stepwise multiple regression analysis showed communication, motor impulsiveness, friends related stress, gender (male), grade (junior high school), explained 30.9% of the total variance in bully victim. Conclusion: The results of this study are expected to be used as basic data in providing a better understanding of adolescents' bullying, in preventing bullying and in developing an intervention program.

• Journal of Environmental Science International
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• v.14 no.11
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• pp.1049-1056
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• 2005

[ $NO_2$ ] concentration characteristics of Busan metropolitan city was analysed by statistical method using hourly $NO_2$ concentration data$(1998\~2000)$ collected from air quality monitoring sites of the metropolitan city. 4 representative regions were selected among air quality monitoring sites of Ministry of environment. Concentration data of $NO_2$, 5 air pollutants, and data collected at AWS was used. Both Stepwise Multiple Regression model and ARIMA model for prediction of $NO_2$ concentrations were adopted, and then their results were compared with observed concentration. While ARIMA model was useful for the prediction of daily variation of the concentration, it was not satisfactory for the prediction of both rapid variation and seasonal variation of the concentration. Multiple Regression model was better estimated than ARIMA model for prediction of $NO_2$ concentration.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.39-50
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• 2006

The flood control offices of main rivers have used a storage function model to forecast flood stage in Korea and studies of flood forecasting actively have been done even now. On this account, the storage function model, which is used in flood control office, regression models and artificial neural network model are applied into flood forecasting of study watershed in this paper. The result obtained by each method are analyzed for the comparative study. In case of storage function model, this paper uses the representative parameters of the flood control offices and the optimized parameters. Regression coefficients are obtained by regression analysis and neural network is trained by backpropagation algorithm after selecting four events between 1995 to 2001. As a result of this study, it is shown that the optimized parameters are superior to the representative parameters for flood forecasting. The results obtained by multiple, robust, stepwise regression analysis, one of the regression methods, show very good forecasts. Although the artificial neural network model shows less exact results than the regression model, it can be efficient way to produce a good forecasts.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.915-922
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• 2013

Quantile regression can estimate multiple conditional quantile functions of the response, and as a result, it provide comprehensive information of the relationship between the response and the predictors. However, when estimating several conditional quantile functions separately, two or more estimated quantile functions may cross or overlap and consequently violate the basic properties of quantiles. In this paper, we propose a new stepwise method to estimate multiple non-crossing quantile functions using constraints on the kernel coefficients. A simulation study are presented to demonstrate satisfactory performance of the proposed method.

• Journal of Korean Academy of Nursing
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• v.33 no.6
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• pp.762-771
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• 2003

Purpose: This study was undertaken in order to determine factors affecting health promoting lifestyle of elderly women. Method: The subjects were 299 elderly community residing women over the age 65 living in 2 large cities. The instruments used for this study were a survey of general characteristics, health promoting lifestyle(47items), perceived health status(6 items), self-efficacy(l7 items), and social support(18 items). The data was analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation coefficients, and Stepwise Multiple Regression. Result: The result of the study are as follows: The average item score for the health promoting lifestyle was 2.46, the highest score on the subscale was interpersonal support(M=2.83). A significant difference between age, education level, income, experience of smoking, alcohol, exercise, and health promoting lifestyle were found. Stepwise multiple regression analysis revealed that the most powerful predictor of health promoting lifestyle was social support(55%). Conclusion: Social support accounted for 54% of the variance in health promoting lifestyle in the elderly women. Therefore, health promoting programs that increase social support should be developed to promote a healthy lifestyle of the elderly women.

• Journal of Korean Academy of Nursing
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• v.34 no.3
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• pp.576-585
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• 2004

Purpose: The purpose of this study was to identify the relationship between eating disorders, physical symptoms, depression and health locus of control. Method: The research design was a descriptive study done by using a constructive self-report questionnaire. A total of 464 elementary school girls were measured. The instrument was a constructive questionnaire that consisted 136 items. The subjects were divided into 4 groups according to the Body Mass Index (BMI). Data analysis was done by SPSS/WIN Programs using frequency, percentage, mean, SD, ANOVA, Pearson correlation coefficient, and stepwise multiple regression. Result: The score of eating disorders differed significantly by BMI : the score was highest in the group of obese students(F=4.208, P=.015). Stepwise multiple regression analysis revealed that the most powerful predictor of eating disorders was BMI. Conclusion: These results indicate that Korean elementary school girls need more education and counseling on diet. Also, we should take systematic efforts to reestablish the social standard of beauty to promote normal growth development.

• Journal of Korean Academy of Nursing Administration
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• v.12 no.4
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• pp.597-603
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• 2006

Purpose: This study was to identify effect of nursing organizational culture on job satisfaction of preceptors. Method: The subjects were 73 preceptors who were working for the 4 of university hospitals in Seoul, Daejeon and Kyong Ki. This study was conducted from Aug to Oct 2005. The data was collected by questionnaires and were analyzed using descriptive statistics, pearson correlation coefficient, stepwise multiple regression. Result: Job satisfaction of preceptors were significantly correlated among nursing organizational culture. The stepwise multiple regression analysis on job satisfaction revealed that nursing organizational culture was a powerful predictor of job satisfaction. Conclusion: The findings indicate that nursing organizational culture is important for improving job satisfaction of preceptors. Therefore it is necessary to develop of good nursing organizational culture for successful preceptorship.

• Journal of Korean Academy of Nursing
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• v.34 no.5
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• pp.702-711
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• 2004

Purpose: The purpose of this study was to identify the relationship among perceived stress, ways of coping, and health promoting behaviors in patients with chronic cardiovascular disease(CCVD). Method: Data was collected by questionnaires from 436 patients with CCVD in a General Hospital in Seoul. The data was analyzed using descriptive statistics, Pearson correlation coefficients, and stepwise multiple regression. Result: The health promoting behavior showed a significant positive correlation with self-efficacy and social support. Also, the health promoting behavior showed a significant negative correlation with perceived stress and symptoms of stress. The stepwise multiple regression analysis revealed that the most powerful predictor of health promoting behaviors was symptoms of stress. Conclusion: A combination of symptoms of stress, social support, self-efficacy, and perceived stress account for 41% of the variance in health promoting behaviors of patients with CCVD. Data from this study suggest that symptoms of stress, social support, ways of coping, and perceived stress are significant influencing factors on health promoting behaviors of patients with CCVD.