• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.91-102
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• 2020

The study investigates the relationship between the inflation rate and economic growth to find out the optimal inflation threshold for economic growth. Therefore, this study applied an ordinary least square model (OLS) and the ordinal regression model, and collected the time-series data from 1996 to 2017 to test the relationship between inflation and economic growth in the short-term and long-term. The sample fits the model and is statistically significant. The study showed that 96.6% of correlation between inflation rate and economic growth are close and 4.5% of optimal inflation threshold is appropriate for economic growth. It finds that the optimal inflation threshold is base to perform economic growth, besides the inflation rate is positively related to economic growth. The results support the monetary policy appropriately. This study identifies issues for Government to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and maintain the inflation and stimulate growth; have appropriate policies to regulate inflation to stimulate economic growth over the long term; set a priority goal for sustainable economic growth; not pursue economic growth by maintaining the inflation rate in the long term, but take appropriate measures to stabilize the inflation at the optimal inflation threshold.

• Journal of Agricultural Extension & Community Development
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• v.30 no.3
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• pp.157-170
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• 2023

This study aims to identify factors that affect the quality of life of rural residents. Data were collected from 4,000 rural residents living in rural areas. Raw data was procured from the 'Survey on Rural Well-being in 2022 in Rural Development Administration'. The main results of the ordinal logit regression analysis are as follows. First, in the case of non-farm households, female, immigrants, more educated, more healthy are more likely to be highly perceived quality of life. In the case of full-time farm households, more healthy are more likely to be highly perceived quality of life. In the case of part-time farm households, younger, married, more healthy are more likely to be highly perceived quality of life. Second, for all rural housholds(non-farmers, full-time farmers, and part-time farmers), local amenities and safety also had positive impact on perception of quality of life.

• Journal of Korean Society for Quality Management
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• v.32 no.3
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• pp.109-125
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• 2004

This paper deals with an optimal process control problem in production of hull structural steel plate with high defective rate. The main quality characteristic(dependent variable) is the internal quality(defect) of plates and is dependent on process parameters(independent variables). The dependent variable(quality characteristics) has three categorical ordinal data and there are 35 independent variables(29 continuous variables and 6 categorical variables). In this paper, we determine the main factors and to develop the mathematical model between internal quality predicted probabilities and the main factors. Secondly, we find out the optimal process condition of main factors through analysis of variance(ANOVA) using simulation. We consider three models to obtain the main factors and the optimal process condition: linear, quadratic, error models.

• Korean Journal of Organic Agriculture
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• v.20 no.1
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• pp.1-19
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• 2012

The purpose of this study is to analyze consumption of homemade organically processed food (HOPF), and to derive directions for consumption promotion of HOPF. A survey was conducted for quantitative analysis regarding consumption. This study used an Ordinal Logistic Regression Model to derive more significant results in analyzing factors of consumption. The findings was that younger consumers with high income are more likely to purchase HOPF. And those consumers with high price and quality contentment are more likely to purchase HOPF. And contentment with certification institutions and improvement of health have a significant positive relationship with consumption. Consumers were found to pay 51 percent more for HOPF than for non-HOPF products. This level show that the current level of price premium for HOPF is 51 percent higher than their desired level. In order to reduce the price premium for HOPF, effective policy programs should be developed. A targeted market strategy to sell HOPF to younger consumers with high income is needed to boost consumption. A strict certification management system should be established to enhance consumer reliability in HOPF.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.203-223
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• 2022

We propose a Bayesian approach to cumulative logistic regression model for the ordinal response based on the orthogonal principal components via singular value decomposition considering the multicollinearity among predictors. The advantage of the suggested method is considering dimension reduction and parameter estimation simultaneously. To evaluate the performance of the proposed model we conduct a simulation study with considering a high-dimensional and highly correlated explanatory matrix. Also, we fit the suggested method to a real data concerning sprout- and scab-damaged kernels of wheat and compare it to EM based proportional-odds logistic regression model. Compared to EM based methods, we argue that the proposed model works better for the highly correlated high-dimensional data with providing parameter estimates and provides good predictions.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.313-322
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• 2005

In this paper, we discuss suppression for logistic regression model. Suppression for linear regression model was defined as the relationship among sums of squared for regression as well as correlation coefficients of. variables. Since it is not common to obtain simple correlation coefficient for binary response variable of logistic model, we consider cumulative logistic models with multinomial and ordinal response variables rather than usual logistic model. As number of category of a response variable for the cumulative logistic model gets collapsed into binary, it is found that suppressions for these logistic models are changed. These suppression results for cumulative logistic models are discussed and compared with those of linear model.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.15 no.2
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• pp.112-117
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• 2004

Background and Objectives : This study is purposed to investigate the statistically significant discrimination model for predicting vocal fold nodule and polyp's lesional grade, with patients' background data and objective voice evaluation parameters. Materials and Method : The retrospective research was carried out at the Ewha Womans University Hospital. 122 patients' voice examination data had been selected, and lesion screening (Grade I, II, and III) was conducted by 2 ENT specialists, with each patient's vocal fold pictures achieved during the laryngoscopy examination. Results : The Lesional Grade Discrimination Model with which the lesional grade of vocal fold nodules and polyps could be predicted was derived by the ordinal logistic regression analysis (using SPSS 10.0). With this model the lesional grades of 73 out of 122 patients(59.8%) were correctly predicted to their formerly screened ones. Conclusion : This model applied the multivariate approach, which statistically combined these currently used parameters, Jitter, Shimmer, MFR, MPT, and patient's background data such as gender and dysphonia period. It might explain the status of benign lesion of vocal folds, and furthermore expect the physiological function of vocal folds.

• Journal of Korean Academy of Nursing
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• v.51 no.1
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• pp.5-14
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• 2021

Purpose: This study aimed to investigate sub-health status (SHS) of people living in China during the Coronavirus disease 2019 (COVID-19) COVID-19 pandemic. COVID-19 is a severe acute respiratory syndrome coronavirus (SARS-CoV) infection-induced acute infectious disease, which is featured by universal susceptibility and strong infectivity, and SHS (a status of low quality health) refers to a status of low-quality health. COVID-19 has gradually developed into a global pandemic, making the public in a high stress situation in physiological, psychological and social states in the short term. Methods: From March 6 to 11, 2020, a large-scale cross-sectional survey was conducted by convenient sampling, and SHS assessment scale was used in the questionnaire. The ordinal logistic regression analysis was used to identify the factors affecting SHS. Results: In this study, 17,078 questionnaires were delivered with 16,820 effective questionnaires collected, and 10,715 subjects (63.7%) were found with SHS, with moderate SHS primarily. Physiological sub-scale scored the highest, followed by psychological and social sub-scales. Ordinal logistic regression analysis indicated that man, only-child, workers and farmers were risk factors of SHS. Protective factors of SHS included living in rural areas and townships, laid-off retirees and education degree. Conclusion: It shows many people in China place in a poor health status during COVID-19 pandemic. It is necessary that relevant departments pay more attention to people with poor health such as men, only-child, urban people, workers and farmers, and groups with high education degree during and after pandemic stabilization.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.591-597
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• 2022

As social anxiety is increasing due to the spread of the COVID-19 epidemic, the responses at the level of local governments are also changing depending on the characteristics. We analyzed the factors influencing perceptions of social safety as they relate to the trustworthiness of local governments. Based on a 2020 social survey of 16 cities, counties, and districts in Busan Metropolitan City, the effects of householder characteristics, economic characteristics, local attachment characteristics, and social safety perception characteristics on the reliability of the local government were analyzed through an ordinal logistic regression analysis. It was found that the more vulnerable the class was and the safer the region was, the higher the trust was in the basic local government. In order to respond and preemptively recover damage in natural and social disaster situations, continuous efforts are needed to strengthen the capabilities of basic local governments.

• Food Science of Animal Resources
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• v.43 no.1
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• pp.113-123
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• 2023

This study investigated the predictability of cooking loss of pork loin through relatively easy and quick measurable quality properties. The pH, color, moisture, protein content, and cooking loss of 100 pork loins were measured. The explanatory variables included in all linear regression models with an adjust-r² value of ≥0.5 were pH and the protein content. In the linear regression model predicting cooking loss, the highest adjust-r² value was 0.7, with pH, CIE L^*, CIE b^*, moisture, and protein content as the explanatory variables. In 30 pork loins, electrical conductivity was additionally measured, and as a result of linear regression analysis for predicting cooking loss, the highest adjust-r² value was 0.646 with electrical conductivity measured at 40 Hz, with pH and color as the explanatory variables. Ordinal logistic regression analysis was performed to predict the three grades (low, middle, and high) of loin cooking loss using pH, color, and 40 Hz electrical conductivity as the explanatory variables, and the percent concordance was 93.8%. In conclusion, the addition of electrical conductivity as an explanatory variable did not increase the prediction accuracy of the linear regression model for predicting cooking loss; however, it was demonstrated that it is possible to predict and classify the cooking loss grade of pork loin through quality properties that can be measured quickly and easily.