• 한국병원경영학회지
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• 제26권4호
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• pp.29-37
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• 2021

Purpose: The purpose of this study is to identify the characteristics and factors affecting falls among elderly inpatients with chronic diseases based on the data from the discharge damage depth survey of the Korea Disease Control and Prevention Agency(KDCA) from 2014 to 2018. Method: The study selected elderly inpatients aged over 65 who were hospitalized(n=1,173). Their data were analyzed after being assigned to either a fall group(KSCD, W00-W19) or a non-fall group. Frequency analysis, cross-tabulation analysis, and binary logistic regression analysis were conducted, using SPSS 28. Results: According to the analysis on category of fall and non-fall group were statistically significant difference in age and having chronic diseases. Based on the binary logistic regression analysis of factors affecting falls, The risk of falls was 1.058 times higher with age, and E11-E14 and I63 as main diagnostic codes, the risk of falls was 2.049 times and 2.437 times higher. Conclusion: It is necessary to develop customized educational manuals and muscle exercise programs considering the characteristics of chronic diseases and to create a safe hospital room environment, and this result is expected to be used as basic data for fall prevention education and manual development for elderly inpatients with chronic diseases.

• 사상체질의학회지
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• 제16권3호
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• pp.18-24
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• 2004

1. Objectives This study is for discovering the characteristics of the sleep in ordinary symptoms based on the Sasang Constitution. The result of this study could be helpful to understand and to identify the patients as Taeumin by contrast with non-Taeumin. 2. Methods There were 1,229 patients(529 men), who answered the questionnaire about their ordinary sleep patterns. They had been diagnosed, including their Sasang Constitution, by the Sasang Constitution specialist at Bundang Oriental Hospital of Dongguk university. Applying the binary logistic regression analysis to each item about ordinary sleep patterns and the diagnosed Sasang Constitution, we can measure the characteristics and influence of ordinary sleep patterns to the dependent variable(Sasang Constitution). 3. Results As a result of the binary logistic analysis on the observed questionnaire, we found the similar features of the ordinary sleep patterns on Taeumin by contrast with non-Taeumin. In order of influence that identify Taeumin or non-Taeumin, first, Taeumin has a tendency that he will snore well or frequently. Second, Taeumin has a tendency that he will not dream, when he sleeps by contrast with non-Taeumin. 4. Conclusions This study will be used to identify patients as Taeumin or non-Taeumin by means of a reference tool.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.577-587
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• 2023

Conventional categorical data imputation techniques, such as mode imputation, often encounter issues related to overestimation. If the variable has too many categories, multinomial logistic regression imputation method may be impossible due to computational limitations. To rectify these limitations, we propose a two-stage imputation method. During the first stage, we utilize the Boruta variable selection method on the complete dataset to identify significant variables for the target categorical variable. Then, in the second stage, we use the important variables for the target categorical variable for logistic regression to impute missing data in binary variables, polytomous regression to impute missing data in categorical variables, and predictive mean matching to impute missing data in quantitative variables. Through analysis of both asymmetric and non-normal simulated and real data, we demonstrate that the two-stage imputation method outperforms imputation methods lacking variable selection, as evidenced by accuracy measures. During the analysis of real survey data, we also demonstrate that our suggested two-stage imputation method surpasses the current imputation approach in terms of accuracy.

• 대한산업공학회지
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• 제40권1호
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• pp.8-17
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• 2014

In this research, we employed various data mining techniques to build predictive models for win-loss prediction in Korean professional baseball games. The historical data containing information about players and teams was obtained from the official materials that are provided by the KBO website. Using the collected raw data, we additionally prepared two more types of dataset, which are in ratio and binary format respectively. Dividing away-team's records by the records of the corresponding home-team generated the ratio dataset, while the binary dataset was obtained by comparing the record values. We applied seven classification techniques to three (raw, ratio, and binary) datasets. The employed data mining techniques are decision tree, random forest, logistic regression, neural network, support vector machine, linear discriminant analysis, and quadratic discriminant analysis. Among 21(= 3 datasets${\times}$7 techniques) prediction scenarios, the most accurate model was obtained from the random forest technique based on the binary dataset, which prediction accuracy was 84.14%. It was also observed that using the ratio and the binary dataset helped to build better prediction models than using the raw data. From the capability of variable selection in decision tree, random forest, and stepwise logistic regression, we found that annual salary, earned run, strikeout, pitcher's winning percentage, and four balls are important winning factors of a game. This research is distinct from existing studies in that we used three different types of data and various data mining techniques for win-loss prediction in Korean professional baseball games.

• 한국환경복원기술학회지
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• 제23권4호
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• pp.13-30
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• 2020

This study aims to analyze the qualitative and quantitative effects of environmental policies in terms of green space management using logistic regression model(LRM). Landsat satellite imageries in 1985, 1992, 2000, 2008, and 2015 are classified using a hybrid-classification method. Based on these classified maps, logistic regression model having a deforestation tendency of the past is built. Binary green space change map is used for the dependent variable and four explanatory variables are used: distance from green space, distance from settlements, elevation, and slope. The green space map of 2008 and 2015 is predicted using the constructed model. The conservation effect of Ulsan's environmental policies is quantified through the numerical comparison of green area between the predicted and real data. Time-series analysis of green space showed that restoration and destruction of green space are highly related to human activities rather than natural land transition. The effect of green space management policy was spatially-explicit and brought a significant increase in green space. Furthermore, as a result of quantitative analysis, Ulsan's environmental policy had effects of conserving and restoring 111.75㎢ and 175.45㎢ respectively for the periods of eight and fifteen years. Among four variables, slope was the most determinant factor that accounts for the destruction of green space in the city. This study presents logistic regression model as a way of evaluating the effect of environmental policies that have been practiced in the city. It has its significance in that it allows us a comprehensive understanding of the effect by considering every direct and indirect effect from other domains, such as air and water, on green space. We conclude discussing practicability of implementing environmental policy in terms of green space management with the focus on a non-statutory plan.

• Journal of Acupuncture Research
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• 제35권4호
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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.

• 대한물리의학회지
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• 제11권3호
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• pp.73-80
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• 2016

PURPOSE: The purpose of this study was to investigate the quality of life related to fall experiences in chronic stroke patients. METHODS: This cross-sectional study included 117 patients with stroke from 3 hospitals in D metropolitan city. General characteristics, including fall experiences and quality of life, were assessed through a face-to-face interviews conducted in a quiet place using a questionnaire. Measurement of quality of life in stroke patients was conducted using the Korean Stroke Specific Quality of Life Scale (SS-QOL). To identify the SS-QOL items related to fall experiences, the items of the SS-QOL were considered as independent variables, and the variables that were significantly different according to fall experiences were identified using a univariate analysis. A binary logistic regression was then performed using fall experiences as the independent variable. RESULTS: According to the univariate analysis, self help activities, social role, and upper extremity function were significantly lower in the fall group than that in the non-fall group (p<.05). The findings of the binary logistic regression confirmed that social roles and upper extremity function were the SS-QOL items that were related to fall experience in chronic stroke patients. CONCLUSION: These findings suggest that social roles and upper extremity function may be risk factors for fall experience in patients with chronic stroke.

• 한국경영과학회지
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• 제33권2호
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• pp.1-16
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• 2008

The purpose of this paper is to propose a new binary classification method for predicting corporate failure based on genetic algorithm, and to validate its prediction power through empirical analysis. Establishing virtual companies representing bankrupt companies and non-bankrupt ones respectively, the proposed method measures the similarity between the virtual companies and the subject for prediction, and classifies the subject into either bankrupt or non-bankrupt one. The values of the classification variables of the virtual companies and the weights of the variables are determined by the proper model to maximize the hit ratio of training data set using genetic algorithm. In order to test the validity of the proposed method, we compare its prediction accuracy with ones of other existing methods such as multi-discriminant analysis, logistic regression, decision tree, and artificial neural network, and it is shown that the binary classification method we propose in this paper can serve as a premising alternative to the existing methods for bankruptcy prediction.

• 한국사회복지학
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• 제49권
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• pp.129-161
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• 2002

This study explores whether there are differences in financial structure and governmental support between social service organizations and other nonprofit organizations. In addition, it analyzes what factors are related to governmental supports for both types of nonprofit organizations. Guided by the argument that specific areas where nonprofits primarily operate can explain a difference of relations between nonprofit organizations and funders, this study compares revenue sources and expenditures of social service organizations and other nonprofit organizations in the United States. Also, based on resource dependence theory and taking some important indexes from financial ratio analysis, this study also identifies factors that affect governmental supports for nonprofit organizations. The study sample consists of 10,690 organizations that reported tax form 990 in 1996. Binary logistic regression analysis was conducted for the study. The results show that social service organizations obtained more revenue from government than other nonprofit organizations. Also, logistic regression analysis suggests that revenue diversification and financial characteristics were significantly associated with governmental supports for nonprofit organizations in the United States.

• 한국치위생학회지
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• 제21권3호
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• pp.227-234
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• 2021

Objectives: The objective of this study was to investigate the relationship between smoking history and periodontal disease among the elderly in South Korea. Methods: The study subjects comprised 2,703 elderly people who underwent oral health examination as part of the 7th South Korea National Health and Nutrition Examination Survey (KNHANES; 2016-2018). Data were analyzed using frequency analysis, Rao-Scott chi-square test, t-test, and binary logistic regression analysis. Results: A complex sample logistic regression analysis showed that the odds for periodontal disease development were higher in past smokers (odds ratio [OR]=1.461; 95% CI=1.070-1.994) and current smokers (OR=1.601; 95% CI=1.011-2.536) than in lifetime non-smokers. Conclusions: Smokers must actively participate in smoking cessation programs and interventions starting from middle age.