• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.5
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• pp.1-13
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• 2020

The empty houses' problem is important in the local revitalization and local sustainability, and these phenomenon caused by various factors of the region. The population and housing census data are the most effective data available to study this phenomenon by small regions. In this study, logistic regression and multiple regression analysis were performed to understand the effects of population, household, and housing characteristics on empty houses using population and housing census data. Also, the scale and direction of the effect of each characteristic in large cities, small cities, and rural areas were compared. As results, there was a slight difference between cities and province regions in the district and housing characteristic variables. In the comparison of Eup-Myeon-Dong, the affected variables were different in the Dong and Myeon areas. The significance of this study is to examine the effect of the characteristics of population and housing on the vacant houses and to confirm that the factors affecting different regions.

• Journal of Acupuncture Research
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• v.35 no.4
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• pp.226-237
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• 2018

Background: This study examined the characteristics and prognosis of patients admitted to the Dunsan Korean medicine hospital for treatment of herniated intervertebral disc (HIVD) or spinal stenosis with Miniscalpel needle therapy (MSN). Methods: Patients were admitted to the Dunsan Korean medicine hospital from January 01, 2016 to September 30, 2017 for the treatment of HIVD or spinal stenosis with MSN. Crossover analysis, Independent sample t test, one-way ANOVA, multiple linear regression analysis, and binary logistic regression analysis were performed. Results: Crossover analysis showed statistically significant differences in treatment methods according to gender, current pain according to the disease duration, satisfaction of MSN according to disease duration, treatment methods, and intention of re-treatment with MSN according to treatment methods. Independent t test and one-way ANOVA showed that there was a difference in current Numeric Rating Scale (NRS) according to disease duration, and difference between discharge and current NRS, and number of MSN according to disease. Multiple linear regression analysis showed that age, disease duration, and number of MSN affect discharge NRS, disease duration, and number of MSN affect current NRS, and Western medical treatment after MSN, discharge NRS, and current NRS affect satisfaction of MSN. Binary logistic regression analysis showed that discharge NRS affects current pain, and gender, discharge NRS, and treatment methods affect intention of re-treatment with MSN. Conclusion: Characteristics, prognosis, satisfaction and variables affecting prognosis of MSN were statistically significant, indicating that more systematic studies are required to further examine the effects of MSN on HIVD or spinal stenosis.

• Clinics in Shoulder and Elbow
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• v.16 no.1
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• pp.63-72
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• 2013

In medical research, multivariate analysis, especially multiple regression analysis, is used to analyze the influence of multiple variables on the result. Multiple regression analysis should include variables in the model and the problem of multi-collinearity as there are many variables as well as the basic assumption of regression analysis. The multiple regression model is expressed as the coefficient of determination, $R^2$ and the influence of independent variables on result as a regression coefficient, ${\beta}$. Multiple regression analysis can be divided into multiple linear regression analysis, multiple logistic regression analysis, and Cox regression analysis according to the type of dependent variables (continuous variable, categorical variable (binary logit), and state variable, respectively), and the influence of variables on the result is evaluated by regression coefficient${\beta}$, odds ratio, and hazard ratio, respectively. The knowledge of multivariate analysis enables clinicians to analyze the result accurately and to design the further research efficiently.

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.135-150
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• 2021

We propose principal differential analysis based classification methods. Computations of squared multiple correlation function (RSQ) and principal differential analysis (PDA) scores are reviewed; in addition, we combine principal differential analysis results with the logistic regression for binary classification. In the numerical study, we compare the principal differential analysis based classification methods with functional principal component analysis based classification. Various scenarios are considered in a simulation study, and principal differential analysis based classification methods classify the functional data well. Gene expression data is considered for real data analysis. We observe that the PDA score based method also performs well.

• Journal of Environmental Impact Assessment
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• v.22 no.3
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• pp.231-240
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• 2013

The Purpose of this research was to propose positioning strategies of urban park (UP) based on the assessment of location characteristics at cheongju city. To do that, this research found out urban park service area (UPSA) using GIS network analysis and built socio-economic attribute database, UP map, and other public service thematic maps such as public transportation, education, child-care, and convenience services. And this research analyzed spatial and attribute data using Pearson's correlation analysis, multiple linear regression, and binary logistic regression methods. As a result of this analysis, 1) the nearer neighborhood park and children's park, the higher land price and assumption income level (AIL). 2) children's parks were closed to living convenience facilities such as bank, hospital, and convenience store. 3) land price, AIL, population, and other public services level (PSL) in UPSA were higher than that of non-UPSA. 4) The higher land price, AIL, population, and other PSL, the higher urban park service level. The results of this research may contribute to resolve the regional UP unbalance and to improve UP service level as public service.

• Journal of Korean Society of Rural Planning
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• v.16 no.2
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• pp.47-55
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• 2010

Land cover and land use change data are important in many studies including climate change and hydrological studies. Although the various theories and models have been developed, it is difficult to identify the driving factors of the land use change because land use change is related to policy options and natural and socio-economic conditions. This study is to attempt to simulate the land cover change using the CLUE model based on a statistical analysis of land-use change. CLUE model has dynamic modeling tools from the competition among land use change in between driving force and land use, so that this model depends on statistical relations between land use change and driving factors. In this study, Yongin, Icheon and Anseong were selected for the study areas, and binary logistic regression and factor analysis were performed verifying with ROC curve. Land cover probability map was also prepared to compare with the land cover data and higher probability areas are well matched with the present land cover demonstrating CLUE model applicability.

• Journal of Korean Neurosurgical Society
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• v.63 no.5
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• pp.640-648
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• 2020

Objective : This study aimed to assess the relationship between increased intracranial pressure (ICP) and mastoid effusions (ME). Methods : Between January 2015 and October 2018, patients who underwent intracranial surgery and had ICP monitoring catheters placed were enrolled. ICP was recorded hourly for at least 3 days. ME was determined by the emergence of opacification in mastoid air cells on follow-up brain imaging. C-reactive protein (CRP) levels, presence of endotracheal tube (ETT) and nasogastric tube (NGT), duration of intensive care unit (ICU) stay, duration of mechanical ventilator application, diagnosis, surgical modalities, and presence of sinusitis were recorded. Each factor's effect on the occurrence of ME was analyzed by binary logistic regression analyses. To analyze the independent effects of ICP as a predictor of ME a multivariable logistic regression analysis was performed. Results : Total of 61 (53%) out of 115 patients had ME. Among the patients who had unilateral brain lesions, 94% of subject (43/50) revealed the ipsilateral development of ME. ME developed at a mean of 11.1±6.2 days. The variables including mean ICP, peak ICP, age, trauma, CRP, ICU stays, application of mechanical ventilators and presence of ETT and NGT showed statistically significant difference between ME groups and non-ME groups in univariate analysis. Sex and the occurrence of sinusitis did not differ between two groups. Adding the ICP variables significantly improved the prediction of ME in multivariable logistic regression analysis. Conclusion : While multiple factors affect ME, this study demonstrates that ICP and ME are probably related. Further studies are needed to determine the mechanistic relationship between ICP and middle ear pressure.

• Nutrition Research and Practice
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• v.13 no.2
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• pp.150-158
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• 2019

BACKGROUND/OBJECTIVES: Inflammation is known to be a risk factor for metabolic diseases. This study aimed to develop a Food-based Index of Dietary Inflammatory Potential (FBDI) and examine its association with metabolic biomarkers. SUBJECTS/METHODS: This study analyzed the raw data from the 2012-2014 Korean Genome and Epidemiology Study data of 17,771 people. To analyze the relationship between foods consumed by Koreans and inflammation, we conducted a correlation analysis between 51 food groups and hs-CRP levels. The FBDI was developed from 17 food groups selected by multiple regression method. We examined whether FBDI was associated with metabolic markers (waist circumference, blood pressure, fasting glucose, triglyceride, and HDL-cholesterol) in the 6th Korea National Health and Nutrition Examination Survey (KNHANES). We used binary logistic regression analysis to examine the association. RESULTS: The FBDI model included seven of the anti-inflammatory food groups and three of the pro-inflammatory food groups. The FBDI formula was calculated by multiplying the intake of food group by ${\beta}$-coefficients derived from the multiple regression model based on the correlation analysis. The FBDI was significantly associated with waist circumference (P < 0.001), blood pressure (P < 0.001), triglyceride level (P < 0.001), and HDL-cholesterol (P < 0.001) level among adults aged 20-64 years in the KNHANES. The prevalence of metabolic syndrome was 2.618 times higher in the group with the highest FBDI than in the group with the lowest one (95% confidence interval: 1.778-3.856, P for trend < 0.001). CONCLUSIONS: This study established an FBDI reflecting food intake patterns of Koreans, which showed a significant relationship with the prevalence of metabolic syndrome.

• Journal of Dental Rehabilitation and Applied Science
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• v.32 no.4
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• pp.280-292
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• 2016

Purpose: The purpose of this study was to compare the long-term survival rate and peri-implant marginal bone loss related to multiple risk factors including the clinician's experience. Materials and Methods: Four hundred twenty implants in 146 patients, who had involved a supportive periodontal therapy program every 3 to 6 months and had follow up data for at least 5 years, were selected as the study group. Peri-implant marginal bone loss, data of demographic, implant and surgical characteristics were collected from peri-apical radiographs and chart review. Implant survival was regarded as the remaining with radiographic marginal bone level in excess of 50% of the fixture length for any reason. Results: The cumulative survival rate after 5 years of loading was 94.9%. In binary logistic regression analysis, smoking status (P = 0.033) and presence of spontaneous cover screw exposure (P < 0.001) were significantly related to 5-year survival of implants. In stepwise multiple regression analysis, smoking status (P < 0.001), type of abutment connection (P < 0.001) and implant surface (P = 0.033) were significantly related to peri-implant marginal bone level. And the year of resident was not statistically related to 5-year implant survival in simple logistic regression analysis (P = 0.171). Conclusion: Smoking status, spontaneous cover screw exposure, type of abutment connection and implant surface might influence the implant success. There was no significant correlation between the year of resident and implant failure.

• Women's Health Nursing
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• v.19 no.1
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• pp.57-65
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• 2013

Purpose: This study identified the effects of body weight control behaviors on bone mineral density (BMD) in Korean women aged 20 to 39 years. Methods: A secondary analysis of the 5th Korean National Health and Nutrition Examination Survey was conducted. Asian-Pacific criteria of BMI (Body Mass Index) and BMD were calculated for 1,026 women selected. The effects of body weight control behaviors were assessed using binary multiple logistic regression analysis while controlling for BMI. Results: Osteopenia and osteoporosis rates were 32.8% and 2.0%, respectively. About 69% of women performed weight control behaviors, and a combination of diet/exercise (22.7%) and drug added methods (10.9%) for weight control. Women who performed both diet control and exercise had a lower possibility to have abnormal BMD than those who did not try weight control (OR=0.67, CI=0.45~0.98, p=.039). Further weight control behaviors did not influence abnormal BMD. Conclusion: Body weight control should include proper diet and exercise in accordance with each woman's BMI level.