• Title/Summary/Keyword: multinomial logistic regression analysis

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Analysis of cause-of-death mortality and actuarial implications

  • Kwon, Hyuk-Sung;Nguyen, Vu Hai
    • Communications for Statistical Applications and Methods
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    • v.26 no.6
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    • pp.557-573
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    • 2019
  • Mortality study is an essential component of actuarial risk management for life insurance policies, annuities, and pension plans. Life expectancy has drastically increased over the last several decades; consequently, longevity risk associated with annuity products and pension systems has emerged as a crucial issue. Among the various aspects of mortality study, a consideration of the cause-of-death mortality can provide a more comprehensive understanding of the nature of mortality/longevity risk. In this case study, the cause-of-mortality data in Korea and the US were analyzed along with a multinomial logistic regression model that was constructed to quantify the impact of mortality reduction in a specific cause on actuarial values. The results of analyses imply that mortality improvement due to a specific cause should be carefully monitored and reflected in mortality/longevity risk management. It was also confirmed that multinomial logistic regression model is a useful tool for analyzing cause-of-death mortality for actuarial applications.

Blur Detection through Multinomial Logistic Regression based Adaptive Threshold

  • Mahmood, Muhammad Tariq;Siddiqui, Shahbaz Ahmed;Choi, Young Kyu
    • Journal of the Semiconductor & Display Technology
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    • v.18 no.4
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    • pp.110-115
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    • 2019
  • Blur detection and segmentation play vital role in many computer vision applications. Among various methods, local binary pattern based methods provide reasonable blur detection results. However, in conventional local binary pattern based methods, the blur map is computed by using a fixed threshold irrespective of the type and level of blur. It may not be suitable for images with variations in imaging conditions and blur. In this paper we propose an effective method based on local binary pattern with adaptive threshold for blur detection. The adaptive threshold is computed based on the model learned through the multinomial logistic regression. The performance of the proposed method is evaluated using different datasets. The comparative analysis not only demonstrates the effectiveness of the proposed method but also exhibits it superiority over the existing methods.

Use of a multinomial logistic regression model to evaluate risk factors for porcine circovirus type 2 infection on pig farms in the Republic of Korea

  • Kim, Eu-Tteum;Pak, Son-Il
    • Journal of Preventive Veterinary Medicine
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    • v.41 no.3
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    • pp.129-132
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    • 2017
  • The current study identified risk factors associated with porcine circovirus type 2 (PCV2) infection on pig farms in the Republic of Korea using a multinomial logistic regression model to evaluate the PCV2 infection status of pigs at different growth stages. Compulsory disinfection of visitors (odds ratio [OR]: 0.019, 95% confidence interval [CI]: <0.001-0.378, p=0.0095), compulsory registration of visitors (OR: 0.002, 95% CI: <0.001-0.184, p=0.0070), regular blood testing (OR: 0.012, 95% CI: <0.001-0.157, p=0.0007), and running on-farm biosecurity learning programs for workers (OR: 0.156, 95% CI: 0.040-0.604, p=0.0072 and OR: 0.201, 95% CI: 0.055-0.737, p=0.0155, respectively) were identified as factors which could reduce the risk of PCV2 infection. However, visitation by a regular veterinarian (OR: 32.733, 95% CI: 3.768-284.327, p=0.0016) was associated with PCV2 infection.

A Study on the Reaction towards Damage Related to Health Foods among the Elderly (노인들의 건강식품 관련 문제 경험에 대한 대응 행동에 관한 연구)

  • Kim, Hyo-Chung;Kim, Mee-Ra
    • Journal of the East Asian Society of Dietary Life
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    • v.18 no.4
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    • pp.608-617
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    • 2008
  • This study examined the level of reaction towards damage related to health foods and the factors affecting this reaction among the elderly. Data were collected from 269 elderly individuals living in Seoul, Daejeon, Daegu, Gwangju and Busan. Frequencies, chi-square tests, and a multinomial logistic regression analysis were performed using the SPSS v. 14.0 program. When asked about their reaction towards damage related to health foods, approximately 48% of the respondents answered 'no response', 34% answered 'private response', and 18% answered 'public response'. Multinomial logistic regression analysis revealed that education level and awareness of health food price were significant factors influencing 'private response', and concerns about health foods and awareness of damage redemption were significant factors for 'public response'. These results imply that consumer education for elderly to prevent damage derived from the purchase and consumption of health foods is required.

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Successful Joint Venture Strategies Based on Data Mining (데이터마이닝 기법을 기반으로 한 성공적인 Joint Venture 전략)

  • Kim, Jin Hyung;Sohn, So Young
    • Journal of Korean Institute of Industrial Engineers
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    • v.33 no.4
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    • pp.424-429
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    • 2007
  • The purpose of this study is to propose types of joint venturesthat can increase the competitivenessof a company in the marketplace. We examine the characteristics of individual venture enterprises based on technology. We considered 16 TEA in order to categorize companies into four groups. Next, we used a multinomial logistic regression model to identify the significant characteristics of a venture company that successfully predicts group membership. Based on this information, we propose various forms of joint venture which complement each other and produce higher overall competence. Our study can provide important feedback information to academics, Policy-makers.

Prediction on Busan's Gross Product and Employment of Major Industry with Logistic Regression and Machine Learning Model (로지스틱 회귀모형과 머신러닝 모형을 활용한 주요산업의 부산 지역총생산 및 고용 효과 예측)

  • Chae-Deug Yi
    • Korea Trade Review
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    • v.47 no.2
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    • pp.69-88
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    • 2022
  • This paper aims to predict Busan's regional product and employment using the logistic regression models and machine learning models. The following are the main findings of the empirical analysis. First, the OLS regression model shows that the main industries such as electricity and electronics, machine and transport, and finance and insurance affect the Busan's income positively. Second, the binomial logistic regression models show that the Busan's strategic industries such as the future transport machinery, life-care, and smart marine industries contribute on the Busan's income in large order. Third, the multinomial logistic regression models show that the Korea's main industries such as the precise machinery, transport equipment, and machinery influence the Busan's economy positively. And Korea's exports and the depreciation can affect Busan's economy more positively at the higher employment level. Fourth, the voting ensemble model show the higher predictive power than artificial neural network model and support vector machine models. Furthermore, the gradient boosting model and the random forest show the higher predictive power than the voting model in large order.

Study on Traffic Accidents Characteristics by using Driver and City Characteristics (로지스틱 회귀분석을 이용한 개인 및 도시 특성에 기반한 교통사고 연구)

  • Jang, Jae Min;Lee, Soong Bong;Lee, Young Ihn
    • International Journal of Highway Engineering
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    • v.20 no.2
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    • pp.97-107
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    • 2018
  • PURPOSES : The effects on traffic accidents change with the changing environment. Accordingly, this study analyzes the characteristics of traffic accidents based on the personal characteristics (gender and age) of drivers, and those of 25 autonomous districts in Seoul, and suggests improvements. METHODS : Based on data pertaining to traffic accidents in Seoul, the analysis of accident characteristics was conducted by categorizing the types of traffic accidents according to the drivers' gender and age, and characteristics of 25 autonomous districts in Seoul. Further, for statistical verification, the SPSS software was used to derive influence variables through a multinomial logistic regression analysis, and a method for reducing traffic accidents was proposed. RESULTS : Analysis results show that males tend to be more involved in speed-related accidents and females in low-experience driving-related accidents such as those during parking and alleyway driving. In addition, variables such as age, automobile type, district, and day of the week are found to influence accident types. CONCLUSIONS : This study analyzed the accident characteristics based on personal and city characteristics to reflect the sociological characteristics that influence traffic accidents. The number of traffic accidents in Korea could be decreased drastically by implementing the results of this study in customized safety education and traffic maps.

Factors Associated with the Method of Feeding Preterm Infants after Hospital Discharge (퇴원 후 미숙아의 수유 유형과 영향요인)

  • Han, Soo-Yeon;Chae, Sun-Mi
    • Child Health Nursing Research
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    • v.24 no.2
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    • pp.128-137
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    • 2018
  • Purpose: To investigate factors that may affect the method of feeding among preterm infants at 4 weeks after discharge. Methods: This study included 222 mother-infant dyads born before a gestational age of 37 weeks. The feeding method and general medical characteristics of the participants were assessed at 4 weeks after discharge using a structured questionnaire. Multinomial logistic regression analysis was used to examine which factors were associated with breastfeeding at home. Results: Of the 222 infants who qualified for the study, 71 (32.9%) continued to receive breastmilk at 4 weeks post-discharge. Multinomial logistic regression analysis showed that breastfeeding at 4 weeks post-discharge was associated with higher breastfeeding self-efficacy, vaginal delivery (experience), direct breastfeeding in the neonatal intensive care unit (NICU), gestational age between 30 and 34 weeks, and breastmilk consumption in the NICU. The following factors were associated with mixed feeding at 4 weeks post-discharge: being employed, having higher breastfeeding self-efficacy, and direct breastfeeding in the NICU. Conclusion: NICU nurses should provide opportunities for direct breastfeeding during hospitalization and support breastfeeding to enhance breastfeeding self-efficacy. These factors may help to ensure the continuation of breastfeeding after discharge. Moreover, factors that affect breastfeeding should be considered when providing interventions.

Analysis of Determinants of Eco-Friendly Food Purchase Frequency Before and After COVID-19 Using the Consumer Behavior Survey for Food (식품소비행태조사를 이용한 COVID-19 전후 친환경식품 구매빈도 결정요인분석)

  • Sung-tea Kim;Seon-woong Kim
    • The Korean Journal of Food And Nutrition
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    • v.36 no.4
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    • pp.222-235
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    • 2023
  • In this research, we examined the shifts in determinants influencing the frequency of eco-friendly food purchases pre- and post-COVID-19. Our analysis utilized filtered 2019-2021 Consumption Behavior Survey data from the Korea Rural Economic Institute Food, excluding any irrational responses. Given the nature of the dependent variable, a multinomial logistic regression model was employed with demographic factors, variables pertaining to food consumption behavior, and variables concerning food consumption awareness as predictors. Following the onset of the COVID-19 pandemic, an individual's level of education was observed to positively influence the frequency of eco-friendly food purchases. In contrast, income level and fluctuations in food consumption expenditure did not appear to have a discernible impact on the purchasing frequency of such eco-friendly products. Irrespective of the advent of COVID-19, variables such as the frequency of online food purchases, the utilization of early morning delivery services, dining out frequency, and the intake of health-functional foods consistently demonstrated a positive correlation with the propensity to purchase eco-friendly foods. Overall, consumers prioritizing safety, quality, and nutrition over price, taste, and convenience in their procurement decisions for rice, vegetables, meat, and processed foods exhibit an increased inclination toward the acquisition of eco-friendly food products.

Associations of Demographic and Socioeconomic Factors with Stage at Diagnosis of Breast Cancer

  • Mohaghegh, Pegah;Yavari, Parvin;Akbari, Mohammad Esmail;Abadi, Alireza;Ahmadi, Farzane
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.4
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    • pp.1627-1631
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    • 2015
  • Background: Stage at diagnosis is one of the most important prognostic factors of breast cancer survival. Because in the breast cancer case this may vary with socioeconomic characteristics, this study was performed to recognize the relationship between demographic and socioeconomic factors with stage at diagnosis in Iran. Materials and Methods: This cross-sectional, descriptive study conducted on 526 patients suffering from breast cancer and registered in Cancer Research Center of Shahid Beheshti University of Medical Sciences from 2008 to 2013. A reliable and valid questionnaire about family levels of socioeconomic status filled in by interviewing the patients via phone. For analyzing the data, Multinomial logistic regression, Kendal tau-b correlation coefficient and Contingency Coefficient tests were executed by SPSS22. Economic status, educational attainment of patient and household head and/or a combination of these were considered as parameters for socioeconomic status. First, the relationship between stage at diagnosis and demographic and socioeconomic status was assessed in univariate analysis then these relationships assessed in two different models of multinomial logistic regression. Results: The mean age of the patients was 48.3 (SD=11.4). According to the results of this study, there were significant relationships between stage at diagnosis of breast cancer with patient education (p=0.011), living place (p=0.044) and combined socioeconomic status (p=0.024). These relationships persisted in multiple multinomial logistic regressions. Other variables, however, had no significant correlation. Conclusions: Patient education, combined socioeconomic status and living place are important variables in stage at diagnosis of breast cancer in Iranian women. Interventions have to be applied with the aim of raising women's accessibility to diagnostic and medical facilities and also awareness in order to reducing delay in referring. In addition, covering breast cancer screening services by insurance is recommended.