• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.547-557
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• 2017

The health-related quality of life data are commonly skewed and bounded with spike at the perfect health status, and the variance tended to be heteroscedastic. In this study, we have developed a prediction model for EQ-5D using linear regression model, beta regression model, and extended beta regression model with mean and precision submodel, and also compared the predictive accuracy. The extended beta regression model allows to model skewness and differences in dispersion related to covariates. Although the extended beta regression model has higher prediction accuracy than the linear regression model, the overlapped confidence intervals suggested that the extended beta regression model was superior to the linear regression model. However, the expended beta regression model could explain the heteroscedasticity and predict within the bounded range. Therefore, the expended beta regression model are appropriate for fitting the health-related quality of life data such as EQ-5D.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.339-353
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• 2024

In cases where the response variable in proportional data is confined to a limited interval, a regression model based on the assumption of normality can yield inaccurate results due to issues such as asymmetry and heteroscedasticity. In such cases, the beta regression model can be considered as an alternative. This model reparametrizes the beta distribution in terms of mean and precision parameters, assuming that the response variable follows a beta distribution. This allows for easy consideration of heteroscedasticity in the data. In this paper, we therefore aim to analyze proportional data using the beta regression model in two empirical analyses. Specifically, we investigate the relationship between smoking rates and coffee consumption using data from the 6th National Health Survey, and examine the association between regional characteristics in the U.S. and cumulative mortality rates based on COVID-19 data. In each analysis, we apply the ordinary least squares regression model, the beta regression model, and the extended beta regression model to analyze the data and interpret the results with the selected optimal model. The results demonstrate the appropriateness of applying the beta regression model and its extended version in proportional data.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2841-2852
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• 2018

This study examines regression modeling method using zero-inflated distribution in relation to estimation of exposure distribution required in advertisement media planning. Exposure distribution is the percentage of audiences that are exposed each time the ad is repeated. Such an exposure distribution plays a very important role in providing basic information necessary for calculating various indicators for quantitatively measuring the advertising effect. Especially, due to the decrease of advertising price and the spread of various media, the frequency of the advertisement or the broadcasting of specific advertisements has been greatly increased compared to the past. As a result, the frequency of exposure is relatively decreasing. In this situation, the number of individuals who are not exposed to the media, that is, are not exposed to advertising structurally is increasing. This research proposes advertising exposure distribution models using a zero-inflated regression model, and conducts a comparative study using actual cases.

• The Korean Journal of Financial Management
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• v.14 no.3
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• pp.157-181
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• 1997

본 연구에서는 우리나라 증시에서 베타 이외에 규모와 장부가/시장가 비율이 수익률의 차이를 설명하는데 유용한가를 실증하고 이를 토대로 13개 산업에 대하여 자본비용을 추정하였다. 1980년에서 1995년 사이의 기간에 대하여 실증한 결과, 우리나라 증시에서 규모요인은 시장위험이 설명하지 못하는 수익률 차이 부분을 상당히 설명하고 있었으나 장부가/시장가 비율은 추가적인 설명력을 보이지 못하였다. 산업별 자본비용을 추정한 결과는 만족스럽지 못하였다. 우선 해당기간 동안에 시장프레미엄이 연 1.33%로 지나치게 낮게 측정되었으며 표준오차는 연 5.85%로 매우 크게 나왔다. 회귀계수의 표준오차를 줄이기 위하여 rolling 회귀분석의 방법을 사용하였지만, 3요인 모형에서 시장위험계수(베타)에 대한 표준오차만 줄어들었을 뿐 나머지 계수들의 표준오차는 오히려 증가하였다. 회귀계수가 지니는 불확실성이 위험프레미엄의 불확실성과 결합되어서 산업별 자본비용에 대한 추정은 매우 부정확하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.329-333
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• 2019

안전한 수공구조물의 설계를 위하여 가장 큰 홍수량이 유발되는 지속시간 즉, 임계지속시간을 적용할 필요가 있다. 임계지속시간은 유역의 지형 인자 특성에 따라 상이 하다. 다양한 연구자들에 의하여 임계지속 시간은 유역의 지형 인자를 고려하여 추정할 수 있고, 이의 추정에 지형 인자를 고려하는 것이 합리적인 것으로 제안하였다. 본 연구에서는 기존에 발표된 임계지속시간 추정에 관련된 연구 성과를 분석하고, 이를 토대로 다양한 지형특성을 포함하고 있는 유역의 하천에 대하여 지형 인자가 임계지속시간을 추정에 기여하는 중요도를 분석하였다. 각 지형 인자의 중요도 판단 지표로는 베타계수를 활용하였다. 형상계수의 크기에 따라 지형 인자의 중요도는 상이 하였다. 임계지속시간을 지형 인자를 활용하여 회귀모형으로 추정할 때 각 인자의 중요도를 고려하여 변수를 선택하면 상관성이 향상될 수 있을 것으로 기대된다.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.472-482
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• 2017

The purpose of this study was to identify the correlations and influence factors of knowledge, attitude, and practice of soldiers on hand washing. This is expected to be basis for hand washing and health education in the army. Total of 420 soldiers were randomly selected and surveyed. The collected data were analyzed using beta regression model through R and SAS program. As a result, there was a statistically significant correlation among knowledge, attitude and practice of hand washing, and the degree of health education was analyzed as having no effect on knowledge, attitude and practice. However, the exposure degree of related health promotional materials had significant effect on them. Therefore, in order to promote the practice of hand washing in the army, continuous exposure of the publicity materials is more effective than the health education. It can be also positively influenced all on knowledge, attitude and practice hand washing.

• The Korean Journal of Financial Studies
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• v.9 no.1
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• pp.245-268
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• 2003

전통적인 방법에 의한 PER는 단순히 그 지표의 일반적인 높고 낮음에 따라 소위 '저평가 종목'이라는 이름으로 투자자들에게 추천되고 있다. 그러나 이런 방법은 개별기업의 구체적 내용을 정확하고 종합적으로 고려하지 못하고 있다. 본 연구는 전통적인 방법으로 사용되는 PER지표의 문제점을 개선코자 배당평가 모형으로부터 도출한 PER지표의 구성요소들을 독립변수로 활용 회귀분석을 했다. 그리고 이를 근거로 이론 지표를 만든 후, 그 이론 지표를 투자의사결정에 적용하였을 때의 유효성을 검증했다. PER지표를 구성하는 독립변수는 Kisor & Whitbeck(1963), Malkiel & Cragg(1970), A. Damodaran(1996)에 의해 연구된 것을 원용, PER지표의 구성요소들로 기업의 배당성향, 이익 성장을, 그리고 위험변수로서의 베타계수를 선정했다. 투자성과는 포트폴리오 투자가 일반적인 현실을 감안해 가치가중수익률을 사용한 포트폴리오의 투자성과를 측정했고, 표본은 국내 거래소 시장에 1991년부터 2001년까지 계속 상장된 금융업종을 제외한 전종목을 대상으로 했다. 실증분석에 사용된 기간은 1997년부터 2001년까지 5년 동안의 자료이며, 투자성과를 검증하기 위한 검증모형으로 위험 프리미엄 모형을 사용했다. 먼저 동 분석기간 중 전통적인 방법에 의한 PER효과는 나타나지 않았고, 아울러 기업규모 효과도 찾을 수 없었다. 그러나 회귀분석을 통해 구해진 이론 지표를 활용할 경우, 이론 지표에 비해 시장 지표가 과소 평가된 그룹이 과대 평가된 그룹과 비교할 때 투자성과가 더 우수한 것으로 나타났다. 또한 이론 지표를 통해 PER수준이 낮아짐에 따라 투자성과가 더 높아지는 PER효과도 발견됐다. 이와 같이 이론 지표에 의해 나타나는 PER효과는 기업규모 효과와는 독립적인 것으로 보인다. 외환위기 이후 우리시장에 나타난 차별화 장세 속에 아직도 PER효과나 기업규모 효과와 같은 시장이례 현상이 존재하는지는 관심의 대상이 됐다고 본다. 본 연구에 의하면 기업규모 효과와는 별개의 PER효과가 여전히 존재하며, 다만 이 PER 효과는 전통적 의미의 일반적으로 낮은 PER종목이 초과수익률을 내는 것이 아니라, 기업규모가 크더라도 그 기업의 개별특성을 고려했을 때 이와 비교해 상대적으로 PER가 낮은 종목에 투자하면 초과수익을 낼 수 있음을 의미한다.

• Journal of the Korean Society of Radiology
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• v.84 no.3
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• pp.638-652
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• 2023

Purpose To investigate the MRI markers for the prediction of amyloid β (Aβ)-positivity in mild cognitive impairment (MCI) and Alzheimer's disease (AD), and to evaluate the differences in MRI markers between Aβ-positive (Aβ [+]) and -negative groups using the machine learning (ML) method. Materials and Methods This study included 139 patients with MCI and AD who underwent amyloid PET-CT and brain MRI. Patients were divided into Aβ (+) (n = 84) and Aβ-negative (n = 55) groups. Visual analysis was performed with the Fazekas scale of white matter hyperintensity (WMH) and cerebral microbleeds (CMB) scores. The WMH volume and regional brain volume were quantitatively measured. The multivariable logistic regression and ML using support vector machine, and logistic regression were used to identify the best MRI predictors of Aβ-positivity. Results The Fazekas scale of WMH (p = 0.02) and CMB scores (p = 0.04) were higher in Aβ (+). The volumes of hippocampus, entorhinal cortex, and precuneus were smaller in Aβ (+) (p < 0.05). The third ventricle volume was larger in Aβ (+) (p = 0.002). The logistic regression of ML showed a good accuracy (81.1%) with mini-mental state examination (MMSE) and regional brain volumes. Conclusion The application of ML using the MMSE, third ventricle, and hippocampal volume is helpful in predicting Aβ-positivity with a good accuracy.

• Journal of Industrial Convergence
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• v.20 no.2
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• pp.11-19
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• 2022

This study examines the role of economic uncertainty in stock price determination in the domestic stock market. To this end, we analyzed the relationship between economic uncertainty indices at home and abroad (USA, China) and stock returns for non-financial companies in Korea from January 2000 to 2017. For the analysis model, the 3-factor model of Fama and French (1992) and the 5-factor model including momentum and liquidity were used. As a result of the analysis, a portfolio with a high beta of economic uncertainty showed higher stock returns than a portfolio with a low beta. This was the same as the US analysis result. Also, the analysis results using the US uncertainty index were more significant than the regression analysis results using the Korean economic uncertainty index.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.3900-3914
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• 2012

This study examined the background of the recent global financial crisis and the concept of one of the financial derivatives such as the credit default swap(CDS) or synthetic CDO(collateral debt obligations), given the rapid growing and changing the over-the-counter derivative markets in their volume and structures. In comparison with the previous literature such as the study of Park & Kim (2011), this research empirically performed more thorough and comprehensive investigations to find any financial characteristics or attributes to determine the CDS spreads. Regarding the results obtained from the multiple regression models, the explanatory variables such as STYIELD3, SLOPE, INASSETS, and VOLATILITY, showed their statistically significant effects on all the tested dependent variables(DVs). Another procedure such as the principle component analysis(PCA), was also performed to account for additional IDVs as possible determinants of the dependent variables. Subsequent to this analysis, larger coefficients of each corresponding eigenvector such as BETA, PFT2, GROWTH, STD, and BLEVERAGE were found to be possible financial determinants. For robustness, all the IDVs were employed to be tested in the 'full' regression model with stepwise procedure. As a result, STYIELD3, SLOPE, and VOLATILITY, and BETA showed their statistically significant relationship with all the dependent variables of the CDS spreads.