• Korean Journal of Psychosomatic Medicine
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• v.15 no.1
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• pp.44-50
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• 2007

Objectives: previous studies have suggested the possible predisposing personality in fibromyalgia(FM). The aim of this study is to investigate the personality traits in female patients with FM compared to healthy female controls using the Temperament and Character Inventory(TCI) and furthermore, to evaluate the personality traits affecting the severity of the symptoms of FM. Methods Forty female patients with FM and 40 healthy female controls were examined using the TCI and the Hamilton depression rating scale. The FM patients were also evaluated the severity of the symptoms of FM using the fibromyalgia impact questionnaire(FIQ). Results : ANCOVA with age and depression levels as covariates showed that the FM patients scored significantly higher on the harm avoidance(F=2.187, p=0.047) and lower on the self-directedness(F=4.551, p=0.036) than the healthy controls. The FIQ scores showed positive correlation with the harm avoidance scores in the FM patients when adjusting for age and depression level(R=0.399, p=0.013) Multiple linear regression models revealed that the harm avoidance scores would affect the FIQ scores in FM patients(95% Cl=0.004-1.942, p=0.049). Conclusions : These results suggest that the female FM patients have distinctive temperament and character dimensions compared to the healthy female controls. Moreover, the harm avoidance may be the predictive personality to affect the severity of the symptoms of female FM patients.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.9 no.3
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• pp.115-124
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• 1997

We measured the variance of eddy diffusion and associated ‘diffusion coefficients’ in coastal regions of Korea by observing the separation distances among multiple drifters deployed simultaneously at the same initial position. The variance of eddy diffusion was found to be proportional to $t^m$, where t is the time and m is a non-integer scaling exponent between 1.5 and 3.5. The observed scaling exponent of eddy diffusion cannot be reproduced by diffusion models employing constant eddy diffusivity. In this study, we applied fractal theory in simulating exponential increase of variance of eddy diffusion. We employed the fGn(fractional Gaussian noise) as a ‘modified’ random walks corresponding to the oceanic eddy diffusion. The variance of eddy diffusion, which corresponds to the fBm(fractional Brown motion) of our diffusion model, is proportional to $t^{2H}$, where H is Hurst scaling exponent. The temporal increase of the variance. with scaling exponent between 1 and 2, was successfully reproduced by our fractal diffusion model. However, our model cannot reproduce scaling exponent greater than 2. The scaling exponents greater than 2 are associated with the velocity shear of the mean flow.

• Economic and Environmental Geology
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• v.53 no.3
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• pp.245-258
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• 2020

In this study, a data-driven response surface method using the results acquired from the numerical simulation is developed to evaluate the potential storage capacity of groundwater due to the construction of a groundwater dam. The hydraulic conductivities of alluvium and basement rock, depth and slope of the channel are considered as the natural conditions of the location for groundwater dam construction. In particular, the probability models of the hydraulic conductivities and the various types of geometry of the channel are considered to ensure the reliability of the numerical simulation and the generality of the developed estimation model. As the results of multiple simulations, it can be seen that the hydraulic conductivity of basement rock and the depth of the channel greatly influence to the groundwater storage capacity. In contrast, the slope of the channel along the groundwater flow direction shows a relatively lower impact on the storage capacity. Based on the considered natural conditions and the corresponding numerical simulation results, the storage capacity estimation model is developed applying an artificial neural network as the nonlinear regression model for training. The developed estimation model shows a high correlation coefficient (>0.9) between the simulated and the estimated storage amount. This result indicates the superiority of the developed model in evaluating the storage capacity of the potential location for groundwater dam construction without the numerical simulation. Therefore, a more objective and efficient comparison for the storage capacity between the different potential locations can be possibly made based on the developed estimation model. In line with this, the proposed method can be an effective tool to assess the optimal location of groundwater dam construction across Korea.

• Journal of Korean Society of Disaster and Security
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• v.13 no.1
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• pp.1-11
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• 2020

One of the important problem in statistical hydrology is to estimate the appropriated probability distribution for a given sample data. For the problem, a goodness-of-fit test is conducted based on the similarity between estimated probability distribution and assumed theoretical probability distribution. Probability plot correlation coefficient test (PPCC) is one of the goodness-of-fit test method. PPCC has high rejection power and its application is simple. In this study, test statistics of PPCC were derived for generalized extreme value distribution (GEV) models based on L-moments and these statistics were suggested by the multiple and nonlinear regression equations for its usability. To review the rejection power of the newly proposed method in this study, Monte Carlo simulation was performed with other goodness-of-fit tests including the existing PPCC test. The results showed that PPCC-A test which is proposed in this study demonstrated better rejection power than other methods, including the existing PPCC test. It is expected that the new method will be helpful to estimate the appropriate probability distribution model.

• Korea Journal of Hospital Management
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• v.18 no.4
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• pp.78-96
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• 2013

The purpose of this study is to analyze the emergency health care utilization using status according to income class. The target was the 2011 data out Korea Health Panel's raw data. 2011 data composed of total 17,035 people from total 5,741 households. This study set total 1,101 adults over full-20-years old having used an emergency health care utilization as its analysis target. In order to find out the number of emergency health care utilization use according to income class and the influential factors on emergency health care utilization cost, this study conducted the multiple regression analysis. And in order to more accurately analyze the emergency health care utilization use status depending on the income class and the features of emergency health care utilization use status, this study developed Models. As the result, this study found following findings. First, as the income class was lower, the gender was male, the age was lower, and the user has spouse, the user was not a business owner or a paid worker, the user is a house owner, the emergency medical facility type was a clinic, the means of transportation was others rather than 119 ambulance, the reason visiting emergency medical facility was belonged to others rather than accidents or poisoning, then the number of emergency was increased. Second, as the user was in higher income class, received the health insurance benefits, the using medical facility was general hospital, used 119 ambulance more often, stay days in emergency was shorter, then health care utilization cost was increased. In this study investigating the data out of Korea Health Panel, it was found that while the number of emergency health care utilization use was increased in the lower income class, but the emergency health care utilization cost was increased for higher income class. It is considered that this finding was caused from the facts that lower income class was more often exposed to dangers for physical health, so the number of emergency health care utilization use was increased, but their health care utilization cost was decreased because of their economic burdens against various examinations and their difficulties to pay such costs, comparing to that of higher income class. Therefore, in order to solve unequal problem of emergency health care utilization use between lower and higher income classs, it is required to set suitable solutions like the disease prevention effort by facilitating national health check-up programs, the enhancement of public health services in quantity and quality, the emergency health care utilization securing policy at using medical facilities, the promotional, educational activities about emergency health care utilization delivery system, the enhanced accessibility of emergency health care utilizations and emergency medical facilities.

• Survey Research
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• v.9 no.2
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• pp.1-27
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• 2008

Problems of incomplete data are pervasive in statistical analysis. In particular, incomplete data have been an important challenge in repeated measures studies. The objective of this study is to give a brief introduction to missing data mechanisms and conventional/recent missing data methods and to assess the performance of various missing data methods under ignorable and non-ignorable missingness mechanisms. Given the inadequate attention to longitudinal studies with missing data, this study applied recent advances in missing data methods to repeated measures models and investigated the performance of various missing data methods, such as FIML (Full Information Maximum Likelihood Estimation) and MICE(Multivariate Imputation by Chained Equations), under MCAR, MAR, and MNAR mechanisms. Overall, the results showed that listwise deletion and mean imputation performed poorly compared to other recommended missing data procedures. The better performance of EM, FIML, and MICE was more noticeable under MAR compared to MCAR. With the non-ignorable missing data, this study showed that missing data methods did not perform well. In particular, this problem was noticeable in slope-related estimates. Therefore, this study suggests that if missing data are suspected to be non-ignorable, developmental research may underestimate true rates of change over the life course. This study also suggests that bias from non-ignorable missing data can be substantially reduced by considering rich information from variables related to missingness.

• Korean Journal of Social Welfare
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• v.66 no.1
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• pp.251-276
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• 2014

This study scrutinizes the common sense in the field of disability employment that the bigger the size of a firm, the lower the employment rate of people with disabilities. This common sense has been established by conventional cross-tabulation and multiple regression analyses without taking into account possible interactions between the sizes of firms and the industries in which they operate. This study shows that the distribution of the disability employment rate violates the linearity and homoscedasticity assumptions of the OLS. In an effort to find models that explain the data better, this study fits the OLS model, the weighted linear regression model, and the multinomial logit model as well as the path analysis which is meant to examine the relationships between firm size and other variables relevant to disability employment. The result shows that, when an interaction term between firm size and industry is added to the model, firm size does not have any significant effect on disability employment rate for those firms with 100 or more regular employees, to the contrary of the findings of prior studies. It also demonstrates that other factors such as job setting, the extent of helpfulness of disability employment employers perceive, employers' care for disability, and employers' awareness of disability policies may matter more than does firm size. This study proposes that future research and policy implementation for disability employment should pay no less attention to industry and other factors mentioned above than to firm size.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.387-397
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• 2015

In this paper, the determinants of the number of job changes in the SMEs (small and medium enterprises) youth-intern project is analysed, utilizing SMEs youth-intern DB and employment insurance DB. Since the number of job changes are count data which take integer values other than negative values, general linear regression analysis becomes inappropriate. Therefore, four models such as Poisson regression model, zero inflated Poisson regression model, negative binomial regression model and zero inflated negative binomial regression model are tried to fit count data. A zero inflated negative binomial regression model is selected to be the best model. Major results are the followings. First, the number of job changes is shown to be significantly smaller in the treatment group than in the control group. Second, the number of job changes turns out to be significantly smaller in the young-age group than in the old-age group. Third, it is also shown that the number of job changes of man is significantly greater than that of woman. Lastly, the number of job changes in the bigger firm is shown to be significantly less than that of the smaller firm.

• Management & Information Systems Review
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• v.37 no.3
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• pp.115-130
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• 2018

The purpose of this study is to clarify the relationship between organizational characteristics and information systems characteristics or job satisfaction, attempts to examine the regulatory effects brought about by the adjustment of social capital theory. So far, The results of this study are based on the analysis of individual models from the perspectives of each functional organization such as HR, organization, finance, operation, and MIS. Therefore, this paper attempted a comprehensive analysis of factors affecting job satisfaction and firm performance by presenting an integrated research model of organizational perspectives in addition to the approach of MIS perspective. The characteristics of information system were promptness, CEO support, and compensation. And the organizational characteristics were multiple regression analysis using innovation, trust, and preferential factors. The analysis data is based on sixth data from the HCCP of Korea Productivity Center. According to the analysis results, all the variables had a significant influence on satisfaction, especially CEO support and trust. The analysis of the moderating effect between innovation and job satisfaction was moderated by vision sharing. Only the logistic regression analysis of the satisfaction with the average salary of the members among the demographic variables was statistically significant. Therefore, this study can be concluded that the overall satisfaction level will be improved by recognizing appropriate compensation as sufficient compensation.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.249-256
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• 2014

Advancing health screening and treatment of cancer techniques, they contribute to grow the probability of survival of cancer patients for a long time. So health behavior and quality of life of the patients are getting important. This study analysed correlation between healthy person and cancer patient's EQ-5D index, social demographic characteristics, health behavior and so on by the multiple regression analysis. The result was that EQ-5D index of cancer patients is lower than healthy persons. Patients of cervical cancer and lung cancer had very low the index especially. In conclusion, cancer have a bad influence on the quality of life. For cancer patients, smoking and drinking are a major factors of correlation. The number of non-smokers among the patients is lower than the number of smokers among healthy persons. This conclusion means that the importance of health behaviors and quality of life for cancer patients is established so that this will be used for basic reference of PHR models and service enhancing quality of life.