• Title/Summary/Keyword: Multiple Factor Analysis

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Minimax Eccentricity Estimation for Multiple Set Factor Analysis

  • Hyuncheol Kang;Kim, Keeyoung
    • Journal of the Korean Statistical Society
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    • v.31 no.2
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    • pp.163-175
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    • 2002
  • An extended version of the minimax eccentricity factor estimation for multiple set case is proposed. In addition, two more simple methods for multiple set factor analysis exploiting the concept of generalized canonical correlation analysis is suggested. Finally, a certain connection between the generalized canonical correlation analysis and the multiple set factor analysis is derived which helps us clarify the relationship.

Robust Parameter Design for Multiple Quality Characteristics using Factor Analysis

  • Kwon, Yong-Man;Chang, Duk-Joon
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.04a
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    • pp.131-139
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    • 2004
  • Robust parameter design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper, we introduce a factor analysis approach to simultaneously optimize multiple quality characteristics in the robust parameter design. An example is illustrated to compare it with already proposed method.

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A Study on Factors Affecting the Use of Ambulatory Physician Services (의사방문수 결정요인 분석)

  • 박현애;송건용
    • Health Policy and Management
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    • v.4 no.2
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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.

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Correlation Analysis between Climate and Contamination Degree through Multiple Regression Analysis (다중회귀 분석을 통한 기후 및 오손도 간의 상관관계 분석)

  • Kim, Do-Young;Lee, Won-Young;Shim, Kyu-Il;Han, Sang-Ok;Park, Kang-Sik
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2003.05e
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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.

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Evaluation of a Traditional Korean Medicine Content Factor and Satisfaction with the Drama "Daejanggeum" (드라마 "대장금"의 한의학 콘텐츠 요소 및 만족도 평가)

  • Kim, Song-Yi;Kim, Ho-Sun;Nam, Min-Ho;Li, Yuejuan;Chung, Hung-Chiang;Park, Hi-Joon;Lee, Hye-Jung;Chae, Youn-Byoung
    • Journal of Acupuncture Research
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    • v.27 no.1
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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.

Relation between Multiple Markers of Work-Related Fatigue

  • Volker, Ina;Kirchner, Christine;Bock, Otmar L.
    • Safety and Health at Work
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    • v.7 no.2
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    • pp.124-129
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    • 2016
  • Background: Work-related fatigue has a strong impact on performance and safety but so far, no agreed upon method exists to detect and quantify it. It has been suggested that work-related fatigue cannot be quantified with just one test alone, possibly because fatigue is not a uniform construct. The purpose of this study is therefore to measure work-related fatigue with multiple tests and then to determine the underlying factorial structure. Methods: Twenty-eight employees (mean: 36.11; standard deviation 13.17) participated in five common fatigue tests, namely, posturography, heart rate variability, distributed attention, simple reaction time, and subjective fatigue before and after work. To evaluate changes from morning to afternoon, t tests were conducted. For further data analysis, the differences between afternoon and morning scores for each outcome measure and participant (${\Delta}$ scores) were submitted to factor analysis with varimax rotation and each factor with the highest-loading outcome measure was selected. The ${\Delta}$ scores from tests with single and multiple outcome measures were submitted for a further factor analysis with varimax rotation. Results: The statistical analysis of the multiple tests determine a factorial structure with three factors: The first factor is best represented by center of pressure (COP) path length, COP confidence area, and simple reaction time. The second factor is associated with root mean square of successive difference and useful field of view (UFOV). The third factor is represented by the single ${\Delta}$ score of subjective fatigue. Conclusion: Work-related fatigue is a multidimensional phenomenon that should be assessed by multiple tests. Based on data structure and practicability, we recommend carrying out further studies to assess work-related fatigue with manual reaction time and UFOV Subtest 2.

Evaluation of the Relationship between the Exposure Level to Mixed Hazardous Heavy Metals and Health Effects Using Factor Analysis (요인분석을 이용한 유해 중금속 복합 노출수준과 건강영향과의 관련성 평가)

  • Kim, Eunseop;Moon, Sun-In;Yim, Dong-Hyuk;Choi, Byung-Sun;Park, Jung-Duck;Eom, Sang-Yong;Kim, Yong-Dae;Kim, Heon
    • Journal of Environmental Health Sciences
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    • v.48 no.4
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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.

Evaluation of Water Quality on the Upstreams of the Soyanggang Dam by using Multivariate Analysis (다변량 분석법을 이용한 소양강댐 상류 유역의 하천 수질 평가)

  • Choi, Han-Kyu;Baek, Hyo-Sun;Heo, Joon-Young
    • Journal of Industrial Technology
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    • v.22 no.A
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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.

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Finite Element Analysis of Subsurface Multiple Horizontal Cracks Propagation in a Half-space Due to Sliding Contact (유한요소법을 이용한 미끄럼 접촉시 내부 복수 수평균열 전파해석)

  • 이상윤;김석삼;권영두
    • Tribology and Lubricants
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    • v.16 no.5
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    • pp.373-380
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    • 2000
  • Finite element analysis is performed on the subsurface crack propagation in brittle materials due to sliding contact. The sliding contact is simulated by a rigid asperity moving across the surface of an elastic half-surface containing single and multiple cracks. The single crack, coplanar cracks and parallel cracks are modeled to investigate the interaction effects on the crack growth in contact fatigue. The crack location is fixed and the friction coefficients between asperity and half-space are varied to analyze the effect of surface friction on stress intensity factor for horizontal cracks. The crack propagation direction is predicted based on the maximum range of shear and tensile stress intensity factors. With a coplanar crack, the stress intensity factor was increased. However, with a parallel crack, the stress intensity factor was decreased. These results indicate that the interaction of a coplanar crack increases fatigue crack propagation, whereas that of a parallel crack decreases it.

Evaluation of User Satisfaction and Image Preference of University Students for Cherry Blossom Campus Trail (대학생들의 캠퍼스 벚꽃터널 산책로 이용 만족도와 이미지 선호도 평가)

  • Lee, In-Gyu;Eom, Boong-Hoon
    • Journal of Environmental Science International
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    • v.28 no.12
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    • pp.1101-1110
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    • 2019
  • This study investigated Post-Occupancy Evaluation (POE) of cherry blossom trails 'Cherry Road' in Daegu Catholic Univ. campus, at Gyeonsan-city, Korea. The evaluation focused on image preference and satisfaction of users i.e., students, using questionnaire surveys. A total 201 questionnaire samples were analyzed and most of the respondents were in the age group of 20. Frequency analysis was conducted on demographics, use behavior, reliability, and means. Factor analysis and multiple regression analysis were conducted for user satisfaction and image preference. Over 80% of visitors came with companions during daytime. The most common motives for use were strolling and walking, event and meeting, passing. For user satisfaction the mean scores were highest for landscape beauty (4.22), image improvement (4.14), campus image (4.08). Night lighting facility received the lowest score (3.32). Factor analysis concerning user satisfaction was categorized into environment-human behavior and physical factors. Multiple regression analysis showed that the overall satisfaction of user was significantly influenced by five independent variables: 'harmonious' (β=.214), 'night lighting facility' (β=.173), 'landscape beauty' (β=.208), 'lawn care' (β=.154), and 'walking trails' (β=.123). The mean scores of image variables were highest for 'beautiful' (5.81), 'bright' (5.67), and 'open' (5.64). The lowest scores was for 'quiet' (4.47). Exploratory factor analysis led to three factors being categorized: aesthetics, comforts, and simplicity. Result of multiple regression analysis indicated that the preference of space image was significantly influenced by five variables: 'bright' (β=.397), 'refreshing' (β=.211), 'cool' (β=.219), 'clean' (β=.182), and 'natural' (β=.-142). Hence, Cherry Road has a high level of user satisfaction and image evaluation, which is interpreted as having various cultural events and value for students on campus. To improve the satisfaction of Cherry Road in the future, it is necessary to secure night lighting, to manage trash cans, and to secure rest space.