• Title/Summary/Keyword: binomial logistic analysis

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A Study on Risk Selection Behavior of Japanese Households: Focusing on the relationship between income level and hyperbolic discount (日本家計のリスク選択行動に関する研究 - 所得水準と双曲性の関係を中心に -)

  • Yeom, Dong-ho
    • Analyses & Alternatives
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    • v.4 no.1
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    • pp.105-123
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    • 2020
  • This study analyzes the risk selection behavior of Japanese households. The study approaches the view of 'the hyperbolic discount' which is used in behavioral economics based on the rise in mortgage lending by low-income households in the late 2000s. The study focuses on how households risk preferences vary by income levels. The study analyzes the relationship of attitude of household interest rate risk using Binomial Logistic and Heckman two-step estimation method assuming that there are only two types of Adjustable-Rate Mortgage and Fixed-Rate Mortgage. As a result of the empirical analysis, low-income households annual income tend to have a higher proportion of housing debt as same as higher interest rate risk preferences households in proportion to income growth and interest rate risk preferences. Those results indicate that there is possibility of a hyperbolic discount on low-income households in Japan, and support the hypothesis that low-income households are relatively higher household debt ratio because of high utility due to home purchase in the near future (short-term).

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Effects of Consumer Awareness of Organic Agricultural Products on Repurchase Intention (유기농산물 소비자인식이 재구매의사에 미치는 영향)

  • Seo, Yong-Sil;Seo, Yoon-Jeong;Lee, Jin-Hong;Lee, Byung-Oh
    • Journal of Distribution Science
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    • v.13 no.11
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    • pp.59-67
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    • 2015
  • Purpose - The number of consumers adopting a lifestyle of health and sustainability has recently increased with the rise of trends in healthy living. The size of the organic agricultural product market has also increased given that these consumers prefer consuming environmentally friendly products that promote family health. However, awareness of organic agricultural products remains insufficient because of the characteristics of the Korean organic agriculture system, which only focuses on food safety inspection. The object of this research is to suggest a policy approach to increase understanding and to expand the purchasing of organic agricultural products by analyzing the influence of customer recognition of such products on their willingness to repurchase. Research design, data, and methodology - This study used binomial logistic regression analysis with the aim of explaining the effects of consumers' socio-demographic characteristics, their awareness of the equivalence arrangement for organic food and of the abolishment of low-pesticide agricultural product certification, and their viewing of negative broadcasts about organic agricultural products on their repurchase intention of such products. A questionnaire survey was conducted with 655 respondents who were in their 20s, lived either in Seoul or in its metropolitan area, and had purchased organic agricultural products. Result - From the results of the analysis, the majority of the respondents recognized organic agricultural products, but they found their prices to be expensive. The majority of the respondents were also aware of the certification system and the reliability of organic agricultural products. However, the results indicate that efforts need to be made to recover consumer trust as many respondents stated that their trust levels in these products were low. In general, those purchasing organic agricultural products were satisfied, but those answering "very satisfied" were not in the majority. Binomial logistic regression analysis results revealed that repurchase intention decreased as consumers viewed a greater number of negative broadcasts about these products. On the other hand, repurchase intention increased as they became more aware of the abolishment of low-pesticide certification. Repurchase intention also increased as income increased, as the number of family members decreased, and when a consumer was a member of a consumer organization. In addition, the older the consumers were who watched the TV programs, the smaller the number of family members that were aware of the abolishment of low-pesticide agricultural product certification and, the higher the income of the consumers aware of organic equivalence arrangement, the greater their repurchase intention. Conclusion - External stimuli, such as negative TV programs on organic agricultural products and the abolishment of the low-pesticide agricultural product certification, relevant social issues and systems, influence consumer repurchase intention. To that end, positive environmental and ecological broadcasting about organic agricultural products would contribute to an increase in purchasing. Additionally, this could be used for promotion and marketing plans as the results indicate that trust in organic agricultural products would cause a positive repurchasing effect.

Analysis-based Pedestrian Traffic Incident Analysis Based on Logistic Regression (로지스틱 회귀분석 기반 노인 보행자 교통사고 요인 분석)

  • Siwon Kim;Jeongwon Gil;Jaekyung Kwon;Jae seong Hwang;Choul ki Lee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.2
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    • pp.15-31
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    • 2024
  • The characteristics of elderly traffic accidents were identified by reflecting the situation of the elderly population in Korea, which is entering an ultra-aging society, and the relationship between independent and dependent variables was analyzed by classifying traffic accidents of serious or higher and traffic accidents of minor or lower in elderly pedestrian traffic accidents using binomial variables. Data collection, processing, and variable selection were performed by acquiring data from the elderly pedestrian traffic accident analysis system (TAAS) for the past 10 years (from 13 to 22 years), and basic statistics and analysis by accident factors were performed. A total of 15 influencing variables were derived by applying the logistic regression model, and the influencing variables that have the greatest influence on the probability of a traffic accident involving severe or higher elderly pedestrians were derived. After that, statistical tests were performed to analyze the suitability of the logistic model, and a method for predicting the probability of a traffic accident according to the construction of a prediction model was presented.

The Relationship between Violation of Designated Lane Usage and Accident Severity on Freeways (고속도로 지정차로제 위반과 교통사고 심각도와의 관계분석: 화물차량을 대상으로)

  • Kim, Joo-Hee;Lee, Soo-Beom;Kim, Da-Hee;Hong, Ji-Yeon
    • Journal of Korean Society of Transportation
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    • v.30 no.3
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    • pp.119-127
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    • 2012
  • For traffic safety, it is imperative for motorists to secure their clear view and to maintain a similar speed with others while driving in a lane. Large-sized vehicles at lower speeds, however, are likely to increase the risk of accident when they share a lane with cars. Although to overcome this complication the Korean Road Traffic Act established rules for the safe use of roads, the reality is that the rules are seldom observed strictly. In this light, this study was designed to analyze the severity of truck-involved accidents, thereby providing justification for the need of truck-designated lanes and thus contributing to measuring road safety more precisely. A binomial logistic regression model was applied to analyze the severity of truck-involved accidents. The analysis showed that several variables affect the severity of truck-involved accidents on freeways; i.e., violation against the rule of truck-designated lanes, weather, difference between daytime and nighttime, and parking on road shoulder. Moreover, the strong enforcement will be needed to make motorists observe the rule, because a Wald statistical test showed that the violation against the rule of truck-designated lanes has the largest influence on the severity.

Analysis of Factors Affecting Satisfaction with Commuting Time in the Era of Autonomous Driving (자율주행시대에 통근시간 만족도에 영향을 미치는 요인분석)

  • Jang, Jae-min;Cheon, Seung-hoon;Lee, Soong-bong
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.5
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    • pp.172-185
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    • 2021
  • As the era of autonomous driving approaches, it is expected to have a significant impact on our lives. When autonomous driving cars emerge, it is necessary to develop an index that can evaluate autonomous driving cars as it enhance the productive value of the car by reducing the burden on the driver. This study analyzed how the autonomous driving era affects commuting time and commuting time satisfaction among office goers using a car in Gyeonggi-do. First, a nonlinear relationship (V) was derived for the commuting time and commuting time satisfaction. Here, the factors affecting commuting time satisfaction were analyzed through a binomial logistic model, centered on the sample belonging to the nonlinear section (70 minutes or more for commuting time), which is likely to be affected by the autonomous driving era. The analysis results show that the variables affected by the autonomous driving era were health, sleeping hours, working hours, and leisure time. Since the emergence of autonomous driving cars is highly likely to improve the influencing variables, long-distance commuters are likely to feel higher commuting time satisfaction.

Human Mastadenovirus Infections and Meteorological Factors in Cheonan, Korea

  • Oh, Eun Ju;Park, Joowon;Kim, Jae Kyung
    • Microbiology and Biotechnology Letters
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    • v.49 no.2
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    • pp.249-254
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    • 2021
  • The study of the impact of weather on viral respiratory infections enables the assignment of causality to disease outbreaks caused by climatic factors. A better understanding of the seasonal distribution of viruses may facilitate the development of potential treatment approaches and effective preventive strategies for respiratory viral infections. We analyzed the incidence of human mastadenovirus infection using real-time reverse transcription polymerase chain reaction in 9,010 test samples obtained from Cheonan, South Korea, and simultaneously collected the weather data from January 1, 2012, to December 31, 2018. We used the data collected on the infection frequency to detect seasonal patterns of human mastadenovirus prevalence, which were directly compared with local weather data obtained over the same period. Descriptive statistical analysis, frequency analysis, t-test, and binomial logistic regression analysis were performed to examine the relationship between weather, particulate matter, and human mastadenovirus infections. Patients under 10 years of age showed the highest mastadenovirus infection rates (89.78%) at an average monthly temperature of 18.2℃. Moreover, we observed a negative correlation between human mastadenovirus infection and temperature, wind chill, and air pressure. The obtained results indicate that climatic factors affect the rate of human mastadenovirus infection. Therefore, it may be possible to predict the instance when preventive strategies would yield the most effective results.

Fitting Cure Rate Model to Breast Cancer Data of Cancer Research Center

  • Baghestani, Ahmad Reza;Zayeri, Farid;Akbari, Mohammad Esmaeil;Shojaee, Leyla;Khadembashi, Naghmeh;Shahmirzalou, Parviz
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.17
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    • pp.7923-7927
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    • 2015
  • Background: The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. Materials and Methods: In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. Results: The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Conclusions: Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

Analyzing the Influence of Policy Measures for Growth Management Plan (성장관리방안 정책수단의 영향력 분석)

  • Jeon, Byung-Chang
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.3
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    • pp.253-268
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    • 2020
  • This study examined the effectiveness of policy measures in a growth management plan by analyzing empirically the influence of regulations and incentives in a non-urban growth management plan of Sejong City using the binomial logistic model. The parcel unit data related development location of Sejong City from 2012 to 2017 was used in the model. The analysis showed that time regulation in the growth management plan has a negative (-) impact on the spread of development, which means it is effective in slowing urban sprawl by lowering the profits of developers. The time regulation applied in Sejong City needs to be used actively in other cities in Korea to prevent urban sprawl. Nevertheless, floor ratio incentives had no influence in inducing development within the growth management area, which means a new incentive policy to meet the local characteristics is needed to strengthen the effectiveness of the growth management plan. This study is meaningful because it attempted an empirical analysis of the effects of the growth management plan at The National Territory Act, and this study could encourage further studies.

Comparison of Determinants of Healthy Food Intake Before and After COVID-19 - Based on 2019~2021 Consumer Behavior Survey for Food - (COVID-19 전후 건강식품 섭취 여부 결정요인 비교 - 2019년~2021년 식품소비행태조사 자료 이용 -)

  • Su-yeon Jung;Na-young Kim;Eun-seo Jeon;Keum-il Jang;Seon-woong Kim
    • The Korean Journal of Food And Nutrition
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    • v.36 no.4
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    • pp.309-320
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    • 2023
  • This study examined the determinants of healthy food purchases before and after COVID-19 in Korea. Binomial and multinomial logistic regression models were applied to Korea Rural Economic Institute's Food Consumer Behavior Survey data from 2019 to 2021. The analysis revealed a significant decrease in the non-intake of healthy food in 2021 compared to 2019, suggesting the impact of COVID-19 on healthy food consumption. Consumption patterns also changed, with a decrease in direct purchases and an increase in gift-based purchases. Several variables showed significant effects on healthy food intake. Single-person households exhibited a higher probability of eating healthy food after COVID-19. The group perceiving themselves as healthy had a lower likelihood of consuming healthy food pre-COVID-19, but this changed after the pandemic. Online food purchases, eco-friendly food purchases, and nut consumption showed a gradual decrease in the probability of non-intake over time. Gender and age also influenced healthy food intake. The probability of eating healthy food increased in the older age group compared to the younger group, and the probability increased significantly after COVID-19. The probability of buying gifts was significantly higher in those in their 60s, indicating that the path to obtaining healthy food differed by age.

Class homogeneous tests with correlation (상관관계가 존재하는 등급별 동질성 검정방법)

  • Hong, Chong Sun;Lee, Na Young
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.1
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    • pp.73-83
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    • 2013
  • Among class quantitative tests for the credit rating systems, the credit rating tests for calibration are to test the class homogeneous differences between observed and predicted probabilities. For one time period, binomial test and chi-square test are included, and normal test and extended traffic lights test are also contained for several time peroids. In this work, we consider real data in which there exists correlation among variables, so that these test methods could be applied to the credit rating systems as well as various kinds of the class data such as BWT data and FSI data.