• 보건행정학회지
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• 제4권2호
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• pp.58-76
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• 1994

In order to study factors affecting the use of the ambulatory physician services. Andersen's model for health utilization was modified by adding the health behavior component and examined with three different approaches. Three different approaches were the multiople regression model, logistic regression model, and LISREL model. For multiple regression, dependent variable was reported illness-related visits to a physician during past one year and independent variables are variaous variables measuring predisposing factor, enabling factor, need factor and health behavior. For the logistic regression, dependent variable was visit or no-visit to a physician during past one year and independent variables were same as the multiple regression analysis. For the LISREL, five endogenous variables of health utiliztion, predisposing factor, enabling factor, need factor, and health behavior and 20 exogeneous variables which measures five endogenous variables were used. According to the multiple regression analysis, chronic illness, health status, perceived health status of the need factor; residence, sex, age, marital status, education of the predisposing factor ; health insurance, usual source for medical care of enabling factor were the siginificant exploratory variables for the health utilization. Out of the logistic regression analysis, health status, chronic illness, residence, marital status, education, drinking, use of health aid were found to be significant exploratory variables. From LISREL, need factor affect utilization most following by predisposing factor, enabling factor and health behavior. For LISREL model, age, education, and residence for predisposing factor; health status, chronic illess, and perceived health status for need factor; medical insurance for enabling factor; and doing any kind of health behavior for the health behavior were found as the significant observed variables for each theoretical variables.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 춘계학술대회 논문집 유기절연재료 방전 플라즈마연구회
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• pp.49-52
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• 2003

The performance of insulators under contaminated conditions is the underlying and the most factor that determines insulation design for outdoor applications, Among the contamination factors, The sea salt is the most dangerous factor, and the salt factor have closed relation with climatic conditions, such as wind, temperature, humidity and so on, Effect of these factors to insulation system is different of each other, and need to show the correlation by multiple regression analysis techniques. In this paper, predicted and analyzed equivalent salt deposit density (ESDD) by change climatic condition through multiple regression analysis.

• Computers and Concrete
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• 제16권3호
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• pp.399-414
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• 2015

Nowadays, fiber reinforced polymer (FRP) composites are widely used for rehabilitation, repair and strengthening of reinforced concrete (RC) structures. Also, recent advances in concrete technology have led to the production of high strength concrete, HSC. Such concrete due to its very high compression strength is less ductile; so in seismic areas, ductility is an important factor in design of HSC members (especially FRP strengthened members) under flexure. In this study, the Adaptive Neuro-Fuzzy Inference System (ANFIS) and multiple regression analysis are used to predict the curvature ductility factor of FRP strengthened reinforced HSC (RHSC) beams. Also, the effects of concrete strength, steel reinforcement ratio and externally reinforcement (FRP) stiffness on the complete moment-curvature behavior and the curvature ductility factor of the FRP strengthened RHSC beams are evaluated using the analytical approach. Results indicate that the predictions of ANFIS and multiple regression models for the curvature ductility factor are accurate to within -0.22% and 1.87% error for practical applications respectively. Finally, the effects of height to wide ratio (h/b) of the cross section on the proposed models are investigated.

• 산업기술연구
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• 제22권A호
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• pp.201-210
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• 2002

The object of this study is to evaluate the factors affecting the water quality and to propose the influence of dominant factor quantitatively. The correlation analysis was performed to know the correlationship among the water quality items As a result of partial correlation analysis, it was shown that the water quality items are affected by the rainfall item directly. The factor analysis was performed to grasp some number of factors on each point for deducing the items of similar variable characteristics. The four points were divided into different factor groups. It was grasped that $NH_3-N$ and $NO_3-N$ Items have different variable characteristics after comparing the items. The Multiple regression analysis can decrease the number of observation. In the deduced multiple regression formula, it was shown that the rate of T-N, $NH_3-N$ and $NO_3-N$ in the independent variable took about 60% among all the regression formulas.

• Corrosion Science and Technology
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• 제19권6호
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• pp.302-309
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• 2020

This study aimed to predict the pitting corrosion characteristics of AL-6XN super-austenitic steel using multiple linear regression. The variables used in the model are degree of sensitization, temperature, and pH. Experiments were designed and cyclic polarization curve tests were conducted accordingly. The data obtained from the cyclic polarization curve tests were used as training data for the multiple linear regression model. The significance of each factor in the response (critical pitting potential, repassivation potential) was analyzed. The multiple linear regression model was validated using experimental conditions that were not included in the training data. As a result, the degree of sensitization showed a greater effect than the other variables. Multiple linear regression showed poor performance for prediction of repassivation potential. On the other hand, the model showed a considerable degree of predictive performance for critical pitting potential. The coefficient of determination (R2) was 0.7745. The possibility for pitting potential prediction was confirmed using multiple linear regression.

• 한국환경보건학회지
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• 제48권4호
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• pp.236-243
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• 2022

Background: In the case of multiple exposures to different types of heavy metals, such as the conditions faced by residents living near a smelter, it would be preferable to group hazardous substances with similar characteristics rather than individually related substances and evaluate the effects of each group on the human body. Objectives: The purpose of this study is to evaluate the utility of factor analysis in the assessment of health effects caused by exposure to two or more hazardous substances with similar characteristics, such as in the case of residents living near a smelter. Methods: Heavy metal concentration data for 572 people living in the vicinity of the Janghang smelter area were grouped based on several subfactors according to their characteristics using factor analysis. Using these factor scores as an independent variable, multiple regression analysis was performed on health effect markers. Results: Through factor analysis, three subfactors were extracted. Factor 1 contained copper and zinc in serum and revealed a common characteristic of the enzyme co-factor in the human body. Factor 2 involved urinary cadmium and arsenic, which are harmful metals related to kidney damage. Factor 3 encompassed blood mercury and lead, which are classified as related to cardiovascular disease. As a result of multiple linear regression analysis, it was found that using the factor index derived through factor analysis as an independent variable is more advantageous in assessing the relevance to health effects than when analyzing the two heavy metals by including them in a single regression model. Conclusions: The results of this study suggest that regression analysis linked with factor analysis is a good alternative in that it can simultaneously identify the effects of heavy metals with similar properties while overcoming multicollinearity that may occur in environmental epidemiologic studies on exposure to various types of heavy metals.

• Journal of Acupuncture Research
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• 제27권1호
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• pp.11-20
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• 2010

Objectives : The study was performed to evaluate a traditional Korean Medicine content in drama "Daejanggeum". Methods : One hundred sixty-nine participants in Taiwan responded to the survey with 10 items, regarding components of success of drama "Daejanggeum". Principal component factor analysis and multiple regression analysis were performed to identify the possible factors to satisfaction with watching drama "Daejanggeum". Results : Factor analysis revealed that dramatic factor(44.8%), content factor(12.3%), and cultural factor(11.3%) were the most important factors to success of drama "Daejanggeum". Multiple regression analysis showed that dramatic factor(beta = .342), content factor(beta = .278), and cultural factor(beta = .131) were associated with the satisfaction with watching drama "Daejanggeum"($R^2$ = .394, with F = 32.280, p<.001). Conclusions : This study demonstrated that dramatic factor, content factor, and cultural factor are the most important factors associated with satisfaction with drama "Daejanggeum" in Taiwan. These findings suggest that a traditional Korean Medicine as a content factor would be very influential in enhancing the possibility of success of drama.

• 한국항해항만학회지
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• 제27권2호
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• pp.163-170
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• 2003

본 연구는 한중정기항로에서 국적선사 활성화 방안에 관한 실증연구이다. 본 연구를 위하여 한중항로의 국적정기선사, 중국적 정기선사, 3국적 정기선사 등의 종사자에 실문지 500매를 배포하여 290매 회수하였으며, 한중정기항로 국적선사 활성화 요인과 물동량 증대효과의 관련성을 검증하기 위하여 먼저, 설문문항의 신뢰성(Reliability)은 크론바하 알파(Cronbach's Alpha)에 의한 내적 일관성 검사법을 통하여 검정하였고, 독립변수의 구성타당성(Construct Validity)을 검정하기 위해서 변수들이 선형결합이라는 가정 하에 요인을 추출하는 주성분 법(Principal Components)을 이용한 요인분석(Factor Analysis)을 실시하였다. 그리고 연구가설을 검증하기 위하여 다변량 회귀분석(Multiple Regression Analysis)을 실시하였다.

• Environmental Analysis Health and Toxicology
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• 제14권3호
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• pp.103-111
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• 1999

To effectively predict the lipophilicity, the aryl hydrocarbon receptor (AhR) affinity, and TEF (Toxic equivalency factor) of dioxins by geometrical descriptors, the multiple linear regression methods with the forward selection and backward elimination were employed with statistical validity. The lipophilicity, the Ah receptor binding affinity, and the toxic equivalency factor of dioxins could be predicted using some geometrical descriptors.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.1513-1514
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• 2013