• Journal of Digital Convergence
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• v.16 no.9
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• pp.279-291
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• 2018

This study is designed to demonstrate risk factors of unmet medical care for people with cerebrovascular disease. To do this, statistical analysis was performed by using hierarchical logistic regression analysis with SPSS/WIN24.0 program using Korean Medical Panel data in 2014. In the final model of the hierarchical logistic regression analysis, which is based on Anderson's Model, adjusted for the factors of the predisposing and enabling factors, the explanatory variables affecting the unmet medical development are gender, economic activity, income level, the experience of lying in a sickbed, restriction on activity, subjective health condition, and the number of chronic diseases. Based on the results of this study, the practical and policy implications for the effective management and treatment of cerebrovascular disease should be included in the countermeasures for cerebrovascular disease, a strategy to reduce the unmet medical incidence of cerebrovascular disease, in order to meet the medical needs, the necessity of comprehensive measures considering various dimensions of variables and the influential variables of unmet medical emergence have been suggested for the necessity of making a detailed service manual that can improve accessibility to medical services.

• Journal of Distribution Science
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• v.20 no.7
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• pp.97-105
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• 2022

Purpose: This study aims to analyze and prove the effect of logistic capability and Total Quality Management practices on Micro, Small and Medium Enterprises (SME) performance directly or mediated by non-financial performance. Research design, data and methodology: This study tested the hypothesis using Hierarchical multiple regression analysis, the method of data collection in this study was using questionnaire, the sampling technique was purposive sampling technique, with SME that has been established for more than 5 years and manufacturing. The data analyzed were 180 respondents using SPSS 25. Results: The findings showed that logistic capability has direct and indirect effects on SME financial performance and has a positive effect on SME financial performance mediated by non-financial performance. While the total quality management practices have a positive effect on SME financial performance mediated by non-financial performance. Thus, companies can achieve maximum financial performance if they invest in developing employee knowledge and concerning on non-financial actions, such as employee satisfaction, innovation and proactively seeking market opportunities. Conclusions: In conclusion, one of the main factors that companies need to consider to improve financial performance is non-financial performance in mediating the effect of logistic capability and TQM practices on the financial performance of SMEs.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.1-10
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• 2013

Hierarchical forecasting strategy does not always outperform direct forecasting strategy. The performance generally depends on demand features. This research guides the use of the alternative forecasting strategies according to demand features. This paper developed and evaluated various classification models such as logistic regression (LR), artificial neural networks (ANN), decision trees (DT), boosted trees (BT), and random forests (RF) for predicting the relative performance of the alternative forecasting strategies for the South Korean navy's spare parts demand which has non-normal characteristics. ANN minimized classification errors and inventory costs, whereas LR minimized the Brier scores and the sum of forecasting errors.

• Journal of Korean Academy of Nursing
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• v.43 no.2
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• pp.225-235
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• 2013

Purpose: This prospective cohort study was done to investigate recall bias to antepartum variables measured at postpartum periods and predictors of postpartum depression. Methods: Participants were 215 women who answered a self-administered questionnaire which included demographics, Postpartum Depression Predictors Inventory-Revised and Korean version of Edinburgh Postpartum Depression Scale at antepartum 36-40 weeks and postpartum 2 weeks and 6 weeks. Data were analyzed using kappa, and hierarchical multiple logistic regression. Results: Agreement between antepartum variables at both antepartum and two postpartum periods was relatively high (${\kappa}$=.55- .95). Postpartum depression rates were 36.3% and 36.7% at two follow-up points. In hierarchical multiple logistic regression analysis, prenatal depression (OR=4.32, 95% CI: 1.41-13.19; OR=5.19, 95% CI: 1.41-19.08), social support (OR=1.40, 95% CI: 1.18-1.66; OR=1.27, 95% CI: 1.06-1.53) and maternity blues (OR=4.75, 95% CI: 1.89-11.98; OR=4.22, 95% CI: 1.60-11.12) were commonly associated with postpartum depression at two follow-up points. Child care stress (OR=1.85, 95% CI: 1.01-3.37) was only associated with postpartum depression at 2 weeks postpartum and pregnancy intendedness (OR=1.57, 95% CI: 1.09-2.27) was only associated with postpartum depression at 6 weeks postpartum. Conclusions: The results indicate a need to apply nursing interventions such as prenatal education and counseling with families from antenatal period.

• Korean Journal of Health Education and Promotion
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• v.26 no.4
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• pp.1-10
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• 2009

Objectives: The purpose of this study is to find the determinants of suicide impulse of residents living in mining region and other areas in one city. The past studies did not examine the suicide related attitudes or behaviors in mining region. This study also examines how coping resources and behaviors moderate the suicide impulse. Methods: For this purpose, hierarchical logistic regression method was used to predict the likelihood of suicide impulse. The personal characteristics, depression, coping resources and behaviors were considered as the independent variables. The data collected in this study was gathered through questionnaire survey with 502 residents in other areas as well as mining area in one city. Results and Conclusion: The results and conclusions are as follows: 1. The chi-square test revealed that residents living mining region showed higher percentage of suicide impulse compared to other areas. 2. The t-test revealed that those with suicide impulse had higher level of depression compared to those without it. This pattern was consistent in other areas as well as mining region. 3. The hierarchical logistic regression revealed that age, education, depression showed positive effect on suicide impulse in mining region. However, in other areas, education, illness, and depression showed positive effect on suicide impulse. Also, this result implies that suicide prevention efforts should be actively made in mining region.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.9-20
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• 2005

Accident type and/or factor identification is important in accident reduction planning. The aim of this paper is to apply the hierarchical approach with binomial distribution and logistic regression analysis to find out types and factors, respectively. Based on 2001 Suwon city black spot data, a binomial distribution modeling approach has been applied to diagnose the black spots, with the help of safety performance modeling approach has been applied to diagnose the black spots, with the help of safety performance function. Then, the logistic regression analysis has been employed to identify the critical factors. Some accident remedies are also reviewed in the light of the model outcomes. The proposed research framework sheds light on a different accident related research and can also be successfully applied to similar studies and sites.

• Journal of Korean Medicine Rehabilitation
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• v.29 no.4
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• pp.89-100
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• 2019

Objectives We are going to analyze patient's medical and Korean medicine use trends after lumbar surgery, and examine the percentage of use of Korean medicine after surgery and its relevance to the medical care outcome after lumbar surgery. Methods Using 3% patients' sample data of the Health Insurance Review and Assessment Service, two groups were compared the treatment progress of the Korean Medicine treatment group and the untreated group after lumbar surgery by hierarchical logistic regression analysis. After hierarchical logistic regression analysis(including propensity scores), two groups were compared after lumbar surgery, the Korean Medicine treatment group within 50days and untreated group within 50days. Results Lumbar surgery was performed in 2750 patients in 2015. It was 3.72 that the risk(odds ratio) of finished treatment of patients treated without Korean Medicine, compared to patients with Korean Medicine. It was 0.12 that the risk of continuing treatment(odds ratio) of patients treated with Korean Medicine within 50 days, compared to patients treatment more than 50 days. Conclusions The ratio of Korean Medicine treatment after lumbar surgery was 14.8%. The group that did not have Korean Medicine showed a higher possibility of treatment termination than the group who did not. Among the groups treated with Korean Medicine, the early treatment group was more likely to end treatment than the late treatment group. Considering various situations in the medical environment, further studies such as prospective studies and long-term data analysis are considered to be necessary.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.203-213
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• 2014

Sickness absence is one of the most important indicators for worker's health and occupational safety and health performance. Sickness absence is primarily depended upon sickness but psycho-social factors in workplace may moderate sickness absence. Even though worker is falling into illness, sickness absence can be prevented by job satisfaction. In Korea it is very difficult to find research output about the association of sickness absence with job satisfaction. This study is planned to investigate the effect of job satisfaction on sickness absence. The third Korean Working Conditions Survey done by Occupational Safety and Health Research Institute in 2011 was used to analyze by logistic regression analysis. The result has shown that job satisfaction has statistically significant effect on sickness absence and simultaneously diminish the effect of symptoms experience on sickness absence. The effect of job satisfaction is greater in short term sickness absence than in long term sickness absence. This study has some limitation because of the cross sectional data of Korean Working Conditions Survey. In future, sophisticated statistical analysis may be done with modelling.

• Women's Health Nursing
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• v.25 no.2
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• pp.207-218
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• 2019

Purpose: To compare reproductive health promoting behaviors (RHPBs) of infertile women with those of normal women and identify effects of RHPB on infertility. Methods: A total of 148 females (73 infertile women and 75 normal women) were enrolled in this study. Measurements included their general characteristics and RHPB using self-report questionnaires. Data were analyzed with descriptive statistics, ${\chi}^2$ test, ANCOVA, and hierarchical logistic regression using SPSS. Results: There were significant difference in incomes, number of family, number of term deliveries, and number of abortions according to infertility diagnosis. Mean duration of infertility was 32.16 months. Only 12.32% women had known cause of infertility. The most common cause of infertility was unknown. Mean RHPB score was 3.98 for infertile women and 4.41 for normal women. In logistic regression, total RHPB (odds ratio [OR], 0.21) and safe sex of RHPB (OR, 0.66) were significant factors influencing infertility. Infertile women's total RHPB and subcategories of RHPB (safe sex behavior and sexual transmitted disease [STD] prevention) were lower than those of normal women. Conclusion: For infertility women, RHPB-related intervention programs are needed, especially information about safe sex behavior and STD prevention.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.141-152
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• 2021

A new statistical model needs additional variables in order to re-evaluate the undecided inference. Then the MNAR assumption is required, since the probabilities for the positivity of the indeterminant and the determinant is calculated differently. In this study, since two statistical models have a hierarchical relationship, we determine the undecided inference under the MNAR assumption using the confidence interval of the difference between two AUCs. Among many methods of estimating the confidence interval of the AUC difference, it is found that four kinds of methods show excellent performance through simulations. And based on these methods, we propose a variable selection method that are useful for the undecided inference using logistic regression models.