• Korea journal of population studies
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• v.30 no.1
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• pp.49-66
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• 2007

본 연구는 2001년 한국에서 사망한 60세 이상 노인들 62,000명의 사망기록 자료를 이용하여 사망원인의 다양성을 보여주는 한편 치매에 의한 사망원인을 가장 잘 예측할 수 있는 변수를 경험적으로 규명하고자 실시하였다. 이와 같은 목적을 위한 연구내용은 다음과 같다. 첫째, 노인들의 주요 사망원인에 해당하는 악성종양, 뇌혈관 질환, 심장병, 당뇨, 만성 호흡기 질환, 치매, 고혈압, 간 질환, 사고, 결핵 및 기타 질병 등 11개 사망원인에 대하여 빈도분석을 실시하였다. 둘째, 60세 이상 사망자들 가운데 치매에 의한 사망원인과 나머지 19개의 사망원인을 비교하여 치매에 의한 사망에 영향을 미치는 요인들을 다항로지스틱회귀분석을 통해 분석하였다. 그 결과, 한국의 노인인구 가운데 연령이 높을수록 치매로 인하여 사망할 가능성(우도비)이 높으며 여성이 남성에 비해 치매에 의하여 사망할 가능성이 높은 것으로 밝혀졌다. 그러나 교육수준이 높을수록 치매에 의하여 사망할 가능성이 낮은 것으로 나타났으며 거주지역은 치매에 의한 사망과 통계적으로 유의미한 관계가 있었으나 일관성은 없는 것으로 밝혀졌다. 한편 결혼지위는 치매에 의한 사망과 통계적으로 유의미한 관계가 없는 것으로 나타났다.

• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.1-8
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• 2014

Recently, use of smartphones has increased so sharply at all ages that addiction problems have emerged. This study analysed factors, focusing on demographic variables, that impact on smartphone addiction of elementary students. First, differences between distributions of addicted groups and those between distributions of most frequently used smartphone functions per variable are analyzed. As a result, grade and academic achievements yield the biggest differences between distributions of addicted groups and gender, grade, and academic achievements yield differences between distributions of most frequently used smartphone functions. Also, differences between distributions of most frequently used smartphone functions per addicted user group are regarded significant. Furthermore, factors affecting smartphone addiction are analysed through the logistic regression analysis and decision trees, where grade, academic achievements, dual-income parents, and residential areas are found affecting in that order.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.373-380
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• 2013

Recently, AR(Augmented Reality) system as an information technology for the increased access of information has a potential possibility of next generation's system for tourism guide. In this regard, the objective of this study is to explore the technology acceptance factors of AR system on tourism destination. To achieve the objective of this study, logit regression model was used to analyze the influential level of the factors. This study was analyzed with the final 224 respondents and the results showed that if there will be assured with high trust and easy access via mobility device as smartphone, the AR system has the possibility of high acceptance level. The result of this study will be expected to be utilized as fundamental data from the viewpoint of the service providers and system developers that want to launch the appropriate service to users' needs of AR system.

• Land and Housing Review
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• v.13 no.1
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• pp.55-65
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• 2022

This paper investigates the distinct characteristics of freehold and leasehold households living in the seven largest cities and the other areas. We employ the two-stage logit regression analysis to identify the marginal effects of wealth and income after controlling for the other one. We document the following results. First, households with more net wealth are more likely to reside in their own houses, regardless of living areas. Second, the pure income effect after controlling for wealth and other variables lowers the tendency of freeholders to live in the seven largest cities while increasing the tendency to live in the other areas. Furthermore, the income effects reduce the tendency to live in the former regions. Our results suggest that the pure income effects enhance preferences for a better living environment (e.g., larger spaces, better school districts, etc.), whereas the wealth effect increases the likelihood of freeholds.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.173-188
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• 2017

This paper aims to analyze the effects of the residential area and personal characteristics of households on the preference of residential location factors. The main results of this study are as follows. Firstly, considering the results of multiple regression analysis, it can be seen that preference of location factors is differentiated according to the residential area and personal characteristics of households by individual location factors. Secondly, considering the results of binomial logistic regression analysis, it can be also elucidated that the preferred location factors are differentiated according to the residential area and personal characteristics of the households. Therefore, it is judged that the residential area and personal characteristics of household and the location factors of the household are mutually influencing each other.

• Journal of Information Management
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• v.42 no.1
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• pp.199-219
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• 2011

Currently, managers and researchers have come to recognize the importance of knowledge as an asset to the organization. Knowledge Management System (KMS) is developed as a tool to manage the organizational knowledge. A significant literature about Knowledge Management in the private, but not public sector. The purpose of the study is to analyze the influencing factors for KMS utilization in a public sector, Jeju Provincial Government Organization. This study performed an empirical research on factors that affect the use of KMS using Knowledge Management system capability and individual & organizational capability criteria. Survey was conducted with 150 employees from Jeju Provincial Government Organization. The Results show that an ability to create knowledge, and knowledge infrastructure are significant factors in determining the level of usage of Knowledge Management system. In particular, the most important factor that influences the usage of Knowledge Management is knowledge creation. and then knowledge infrastructure. The result also shows that the usage of KMS is affected by management's support willingness.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.345-352
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• 2019

This paper examines the opportunistic behavior of corporate insiders and analyzes the relationship between equity change and the possibility of delisting. The findings are summarized as follows. First, the larger the stake reduction of insider, the greater the negative excess return after announcement. In the delisting firm group, there is a significant decrease in equity and statistically significant results in the difference test between the comparative groups. The logistic regression analysis showed that the regression coefficient of equity change was negatively statistically significant, indicating a significant correlation between insider share change and the possibility of delisting. These findings are expected not only to provide useful information for investors, but also to be evidence of capital market information asymmetry.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.859-869
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• 2011

Interest has increased in academic research regarding key factors that drive box-office success as well as the ability to predict the box-office success of a movie from a commercial perspective. This study analyzed the relationship between key success factors of a movie and box office records based on movies released in 2010 in Korea. At the pre-production investment decision-making stage, the movie genre, motion picture rating, director power, and actor power were statistically significant. At the stage of distribution decision-making process after movie production, among other factors, the influence of star actors, number of screens, power of distributors, and social media turned out to be statistically significant. We verified movie success factors through the application of a Multinomial Logit Model that used the concept of choice probabilities. The Multinomial Logit Model resulted in a higher level of accuracy in predicting box-office success compared to the Artificial Neural Network and Discriminant Analysis.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.367-382
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• 2018

Prediction models for a corporate bond rating in existing studies have been developed using various models such as linear regression, ordered logit, and random forest. Financial characteristics help build prediction models that are expected to be contained in the assigning model of the bond rating agencies. However, the ranges of bond ratings in existing studies vary from 5 to 20 and the prediction models were developed with samples in which the target companies and the observation periods are different. Thus, a simple comparison of the prediction accuracies in each study cannot determine the best prediction model. In order to conduct a fair comparison, this study has collected corporate bond ratings and financial characteristics from 2013 to 2017 and applied prediction models to them. In addition, we applied the elastic-net penalty for the linear regression, the ordered logit, and the ordered probit. Our comparison shows that data-driven variable selection using the elastic-net improves prediction accuracy in each corresponding model, and that the random forest is the most appropriate model in terms of prediction accuracy, which obtains 69.6% accuracy of the exact rating prediction on average from the 5-fold cross validation.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1997.11a
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• pp.331-336
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• 1997

본 연구에서 산업재해 사례를 연구 대상으로 재해 발생의 여러 가지 요인들의 관련을 검토하고자 통계적 기법을 이용한 재해요인별 상관분석, 또는 영향의 정도 파악, 재해 요인의 통제에 따른 기타 재해요인에 대한 영향 분석을 시도하는 통계학적 분석 방법을 이용한 재해 발생의 중요요인을 분석하고자 첫째, 산업재해 통계 자료의 내용을 분석하여 재해 관련 변수들을 파악하는데 불안전 행동 및 불안전상태에 의한 재해 형태와 기타 변수들 간의 정성적 상관분석을 통한 상관계수를 고찰, 둘째, 명목척도인 범주형 변수 상호 간의 관련 여부를 파악하기 위해 카이제곱(chi-square)검정을 행하여 입원 일수를 종속 변수로 하는 기타 변수들의 독립성 여부와 변수 상호간 연관이 있다고 판단될 때 각 변수의 연관의 정도 비교, 셋째, 어떤 변수 상호간 일정한 관계를 가질 때 변수의 범주별로 반응변수(종속변수)에 미치는 영향을 회귀식 형태로 파악하고 비교하기 위하여 로짓(logit)모형을 적용하였다. (중략)