• The Korean Journal of Emergency Medical Services
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• v.20 no.1
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• pp.17-30
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• 2016

Purpose: This study investigated factors related to empowerment of paramedic students. Methods: A total of 208 students in the department of emergency medical services who experienced clinical practice at 5 universities were selected by convenience sampling methods. Differences in empowerment by general and major-related characteristics were evaluated using a t-test and analysis of variance. The association between satisfaction with clinical practice and empowerment was tested using correlation coefficients. Multiple linear regression analysis was performed to investigate the factors associated with empowerment. Results: The levels of overall satisfaction with clinical practice and empowerment were 107.48 and 99.46, respectively. In simple analysis, empowerment level was associated with general characteristics, major-related characteristics, characteristics of clinical practice, and satisfaction with clinical practice. Empowerment level was significantly higher in older subjects (${\beta}=5.282$, p = .023), subjects with very good (${\beta}=8.487$, p = .002) or fair (${\beta}=4.879$, p = .010) subjective health status, and high subjective school record (${\beta}=5.837$, p = .008) in multiple linear regression analysis. Satisfaction with clinical practice was positively associated with empowerment (${\beta}=0.250$, p < .001). Conclusion: Empowerment was associated with major-related factors and satisfaction with clinical practice. Increased satisfaction with clinical practice could positively influence empowerment for paramedic students.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.5
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• pp.533-542
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• 2010

The $PM_{10}$ concentrations in the underground should be monitored for the health of commuters on the underground subway system. Seoul Metro and Seoul Metropolitan Rapid Transit Corporation are measuring several air pollutants regularly. As for the measurement of $PM_{10}$ concentrations, instruments based on $\beta$-ray absorption method and gravimetric methods are being used. But the instruments using gravimetric method give us 20-hour-average data and the $\beta$-ray instruments can measure the $PM_{10}$ concentration every one hour. In order to keep the $PM_{10}$ concentrations under a healthy condition, the air quality of the underground platform and tunnels should be monitored and controlled continuously. The $PM_{10}$ instruments using light scattering method can measure the $PM_{10}$ concentrations every less than one minute. However, the reliability of the instruments using light scattering method is still not proved. The purpose of this work is to study the reliability of the instruments using light scattering method to measure the $PM_{10}$ concentrations continuously in the underground platforms. One instrument using $\beta$-ray absorption method and two different instruments using light scattering method (LSM1, LSM2) were placed at the platform of the Jegi station of Seoul metro line Number 1 for 10 days. The correlation between the $\beta$-ray instrument and the LSM2 ($r^2$=0.732) was higher than that between the $\beta$-ray instrument and the LSM1 ($r^2$=0.393). Thus the LSM2 was chosen for further analysis. Three different regression analysis methods were tested: Linear regression analysis, Nonlinear regression analysis and Orthogonal regression analysis. When the instruments using light scattering method were used, the data measured these instruments have to be converted to actual $PM_{10}$ concentrations using some factors. With these analyses, the factors could be calculated successfully as linear and nonlinear forms with respect to the data. And the orthogonal regression analysis was performed better than the ordinary least squares method by 28.45% reduction of RMSE. These findings propose that the instruments using light scattering method light scattering method can be used to measure and control the $PM_{10}$ concentrations of the underground subway stations.

• Journal of the Korean Statistical Society
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• v.7 no.2
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• pp.101-104
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• 1978

This paper considers the problem of estimating $\hat{\beta}$ in the case errors occur in observing the values of q-variables $X_1, X_2, ..., X_q$. The approximated estimator $\hat{\beta}(e)$ is obtained and its expected value, bias and covariance matrix are studied.

• Journal of the Korean Society of Food Culture
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• v.24 no.6
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• pp.711-720
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• 2009

The purpose of this study was to understand the effects of hotel employees' physical attractiveness on person-job fit and to empirically analyze whether self-esteem and self-efficacy play a mediating role in the causality between an employee's physical attractiveness and person-job fit. Self-administered questionnaires were completed by 345 employees and the data were analyzed by frequency analysis, factor analysis, reliability analysis, correlation analysis and multiple regression analysis. The primary results were as follows: Multiple regression analysis showed that hotel employee physical attractiveness had a positive significant influence on self-esteem ($\beta=.504$, p<.001) and self-efficacy ($\beta=.441$, p<.001). Also, employee selfesteem ($\beta=.281$, p<.001) and self-efficacy ($\beta=.478$, p<.001) each had a positive significant influence on person-job fit. As a result of analyzing the mediating role, the effect of hotel employees' physical attractiveness on person-job fit was partially mediated by self-esteem and self-efficacy.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.339-353
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• 2024

In cases where the response variable in proportional data is confined to a limited interval, a regression model based on the assumption of normality can yield inaccurate results due to issues such as asymmetry and heteroscedasticity. In such cases, the beta regression model can be considered as an alternative. This model reparametrizes the beta distribution in terms of mean and precision parameters, assuming that the response variable follows a beta distribution. This allows for easy consideration of heteroscedasticity in the data. In this paper, we therefore aim to analyze proportional data using the beta regression model in two empirical analyses. Specifically, we investigate the relationship between smoking rates and coffee consumption using data from the 6th National Health Survey, and examine the association between regional characteristics in the U.S. and cumulative mortality rates based on COVID-19 data. In each analysis, we apply the ordinary least squares regression model, the beta regression model, and the extended beta regression model to analyze the data and interpret the results with the selected optimal model. The results demonstrate the appropriateness of applying the beta regression model and its extended version in proportional data.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.113-117
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• 2016

Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (${\beta}$=0.13, p-value<0.001), for colorectal cancer was in the 75th percentile (${\beta}$=0.048, p-value<0.001), for prostate cancer the 95th percentile (${\beta}$=0.55, p-value<0.001), for lung cancer was in 95th percentile (${\beta}$=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (${\beta}$=0.011, p-value<0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(${\beta}$=0.003, p-value<0.001), for esophageal cancer the 95th (${\beta}$=0.04, p-value=0.4) and for skin cancer also the 95th (${\beta}$=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made.

• Journal of the Korean Society of Child Welfare
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• no.26
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• pp.87-111
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• 2008

The purpose of this study is to evaluate the actual conditions of peer victimization and to examine how the various factors of school climate influence peer victimization. Analysis on the relationship between various school climate and peer victimization has not been yet dealt with in Korea. Participants in this study were middle school students chosen from 11 middle schools in Seoul, by convenience sampling. A total of 1,204 surveys were then analyzed. Methods for analysis included Frequencies, Descriptives, Pearson's Correlation, Hierarchical Regression. From the result of the analysis, the level of verbal violence came out to be a relatively high form of peer victimization. The hierarchical regression were conducted in two steps. The second model's descriptive variable was higher by 19.6% than the first model. The variables of interaction between teacher and student in peer violence(${\beta}=.130$), of school facility maintenance(${\beta}=.067$), of safety of school environment(${\beta}=.331$), and economic status and sex out of controlled variables were proved to be of significance, and those variables explained 23.0% of the entire model. Based on the results of this study, practical and effective policy solutions to improve the school climate better have been suggested.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.89-97
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• 2016

The purposes of this study was to identify the significant predictors of depression. The data were collected using questionnaire from the sample of 114 middle-aged women and 125 middle-aged men. The data were collected through self-report questionnaires, which were constructed to include stress, self-esteem, and depression. Data were analyzed using frequencies, means, $X^2$-test, Analysis of Covariance, Pearson's correlation coefficients, and multiple regression analysis with SPSS 18.0. The significant predictors of depression for middle-aged women were stress(${\beta}=.387$, p<.001), self-esteem(${\beta}=-.249$, p<.05), health perception(${\beta}=-.191$, p<.05), explaining 43.1% of the variance in depression. The significant predictors of depression for middle-aged men were self-esteem(${\beta}=-.429$, p<.001), stress(${\beta}=.322$, p<.001), explaining 56.0% of the variance in depression.

• International Journal of Advanced Culture Technology
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• v.6 no.2
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• pp.72-79
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• 2018

The purpose of this study was to analyze general characteristics and empathy factors of nursing student's major satisfaction. Participants in this study were 235 students from both located in J do and C do Universities. The research method was a cross-sectional survey and the survey period was from September 1 to 10, 2017. The questionnaire was used to investigate general characteristics, empathy, and major satisfaction. The analysis was based on frequency analysis, p value of t or F value, Pearson correlation, regression analysis, and hierarchical regression analysis using SPSS 18.0. The result of this study were as follows: (1) The C University showed higher satisfaction than J University(3.44), (2) the factors affecting major satisfaction were school location, grade, religion, cognitive empathy, and emotional empathy correlated, Regression analysis was used to examine factors that correlated with major satisfaction, followed by hierarchical regression analysis to identify the most influential factors. (3) The result of the analysis showed that the greatest influence factors on major satisfaction were the University location(${\beta}=.325$, p<.01), the cognitive empathy (${\beta}=.287$, p<.01), and the next order was negative grade(${\beta}=-.230$, p<.01). Based on the results of this stud, the following conclusions can be drawn. The most influential factor in the major satisfaction was the school location, but this was an irreversible factor. Therefore, if the cognitive empathy factor and grades are corrected, it can be said that it can increase the satisfaction of major in nursing University students. In this study, it was emphasized that cognitive empathy contained in the course of nursing education program and suggested guidance on major satisfaction in lower grades.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.237-246
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• 2019

Purpose: The purpose of this study is to examine the factors influencing dating violence in University students. Methods: A descriptive regression design was used and the participants were 211 university students. Data analysis included t-test, ANOVA, pearson's correlations, multiple regression. Results: The significant factors affecting dating violence were justification of violence and irrational belief of date violence. The regression model explained approximately 24.7~33.0 % of dating violence. Conclusion: The findings recommend that nurses have to improve preventing dating violence of university students by considering violence perception.