• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.521-531
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• 2002

Various diagnostic techniques for identifying influential observations are mostly based on the deletion of a single observation. While such techniques can satisfactorily identify influential observations in many cases, they will not always be successful because of some mask effect. It is necessary, therefore, to develop techniques that examine the potentially influential effects of a subset of observations. The partial regression plots can be used to examine an influential observation for a single parameter in multiple linear regression. However, it is often desirable to detect influential observations for a subset of regression parameters when interest centers on a selected subset of independent variables. Thus, we propose a diagnostic measure which deals with detecting influential observations on a subset of regression parameters. In this paper, we propose a measure M, which can be effectively used for the detection of influential observations on a subset of regression parameters in multiple linear regression. An illustrated example is given to show how we can use the new measure M to identify influential observations on a subset of regression parameters.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.415-422
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• 2017

Finding influential factors from given clustering result is a typical data science problem. Genetic Algorithm based method is proposed to derive influential factors and its performance is compared with two conventional methods, Classification and Regression Tree (CART) and Chi-Squared Automatic Interaction Detection (CHAID), by using Dunn's index measure. To extract the influential factors of preference towards political parties in South Korea, the vote result of $18^{th}$ presidential election and 'Demographic', 'Health and Welfare', 'Economic' and 'Business' related data were used. Based on the analysis, reverse engineering was implemented. Implementation of reverse engineering based approach for influential factor analysis can provide new set of influential variables which can present new insight towards the data mining field.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.4
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• pp.9-18
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• 2002

This study investigated the influential range of landmarks and the relationship between landmarks and cognition factor so as to offer basic data to be used for the effective use and the management of landmarks. In this study, eighteen famous landmark in Seoul were selected and analyzed. The result of this study can be summarized as follows : 1) First, eighteen determining elements of cognition factors were selected via documents survey. Second, general cognition factors of landmarks were analysed using these elements through questionnaires to specialists. As a result of factor analysis, historic cultural factor, scale factor, visual form factor, locational factor and uniqueness factor were revealed. 2) According to revealed cognition factor, eighteen landmarks are categorized into four types using MDS method via questionnaire to resident in Seoul city. These four types of landmarks are: type I that are recognized by historic cultural factor; type II that are recognized by scale factor; type III that are recognized by uniqueness factor; and type IV that are recognized by visual form factor. 3) As the result of regression, the influential range of landmarks were revealed at about a 10km radius(type I : 12km type II : whole area of Seoul city≒15km, typeIII : 8.7km, typeIV : 8.5km). 4) As a result of analysing the correlation between the influential range and the cognition factor through multiple linear regression analysis, the locational factor is the main factor affecting the influential range of landmarks in every type. The uniqueness factor comes next, which affects influential range partially. 5) Except type 1, as a result of analysing the correlation between influential range and the physical heights of landmarks, a quadratic equation is revealed, showing that the influential range of landmarks over 200 meters in height shows a radical change. Landmarks can be used as reinforcement tools of legibility, effective tools for landscape management and for the improvement of a community's image. This study on the influential range of landmarks and main cognition factor can be utilized as a landmark management plan and in urban planning, such as a new town plan.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.197-212
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• 2002

When assessing goodness-of-fit of a model, a small subset of deviating observations can give rise to a significant lack of fit. It is therefore important to identify such observations and to assess their effects on various aspects of analysis. A Cook's distance measure is usually used to detect influential observation. But it sometimes is not fully effective in identifying truly influential set of observations because there may exist masking or swamping effects. In this paper we confine our attention to influential subset In GLMs such as logistic regression models and loglinear models. We modify a backwards stepping algorithm, which was originally suggested for detecting outlying cells in contingency tables, to detect influential observations in GLMs. The algorithm consists of two steps, the identification step and the testing step. In identification step we Identify influential observations based on influencial measures such as Cook's distances. On the other hand in testing step we test the subset of identified observations to be significant or not Finally we explain the proposed method through two types of dataset related to logistic regression model and loglinear model, respectively.

• The Korean Journal of Rehabilitation Nursing
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• v.17 no.2
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• pp.64-71
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• 2014

Purpose: The purpose of this study was to identify the quality of recovery and influential factors on the quality of recovery after cardiac surgery. Methods: 198 patients undergone cardiac surgery were asked to fill in a self-reported questionnaire about the quality of recovery, anxiety, depression including social support at discharge. The collected data were analyzed with mean, standard deviation, correlation and stepwised multiple regression. Results: The mean scores of quality of recovery at discharge after cardiac surgery was 2.04 on a 3 point scale. Influential factors on the quality of recovery after cardiac surgery were depression(p=.001) and anxiety(p=.027), which disclosed 44.2% of explanation. Depression was the most influential factor. Conclusion: The influential factors on the quality of recovery at discharge after cardiac surgery were depression and anxiety. More studies will be required to reduce depression and anxiety in patients undergone cardiac surgery.

• Hwankyungkyoyuk
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• v.23 no.1
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• pp.50-63
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• 2010

This study is a qualitative case study aiming at understanding and finding out influential factors and barriers when school teachers choose Environmental Education as their Creative Discretionary Activities. To do this, this study focuses on the process of two teachers' choices of the Creative Discretionary Activities in two other elementary schools. The results of this research are follows. Two teachers' choices are affected by several influential factors, divided into external factors and internal factors. External influential factors include culture of school and education, media, chief education officers, parents and school. Internal influential factors are teachers' value and philosophy of education, teachers' experiences, teachers' capacity. These influential factors' forces aren't the same with each other. These influential factors, are influenced by educational, social, national, local, and school level indicated by Taylor et al's (1974) classification criterion. Especially, however, Korea's particular educational environment focusing on university entrance examination strongly affects teachers' choice. School factors also has a big strong effect on teachers' choice. Among others internal actors are the most serious influential factor affecting on teachers' choice.

• Journal of Korean Society for Quality Management
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• v.16 no.2
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• pp.18-33
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• 1988

A new diagnostic statistic for detecting outliers and influential observations in linear models is suggested and studied in this paper. The proposed statistic is a weighted sum of two measures ; one is for detecting outliers and the other is for detecting influential ovservations. The merit of this statistic is that it is possible to distinguish outliers from influential observations. This statistic can be used for not only regression models but also factorial design models. A Monte Carlo simulation study is reported to suggest critical values for detecting outliers and influential observations for simple regression models when the number of observations is 11. 21, 31, 41 or 51.

• Journal of Korean Home Economics Education Association
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• v.9 no.2
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• pp.161-174
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• 1997

The purpose of this study is to investigate the effects of self-concept, reference group, consumer education, and materialism on the propensity for conspicuous consumption of adolescents. The data used in this study were collected through questionnaires on 604 adolescents living in Cheju City. The data were analyzed by using SPSS PC(sup)+ program. The propensity for conspicuous consumption of adolescents differed significantly according to their age and allowance, and sex. The propensity for conspicuous consumption of the middle school students was higher than that of the high school students. The propensity for conspicuous consumption of boys was higher than of girl’s. The propensity for conspicuous consumption of the adolscents was influenced by materialism and the reference group. According to the results of the multiple regression analysis, the most influential factor was materialism and reference group. In clothing materialism was the most influential factor and the reference group was the second influential factor. But In shoes, bag, and school supplies the reference group was the most influential factor and materialism was the second influential factor.

• Korean Journal of Human Ecology
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• v.3 no.1
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• pp.40-50
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• 2000

The purpose of this study is to investigate the influential variables related to the value orientation and environmental preservation behavior. This study is also to provide data for environment education. The subjects were 538 children, in June. 1998, in Kwangju. The data obtained were analyzed by Pearson's correlation. Cronbach's u coefficient. multiple regression. and Path analysis. The major findings were as follows : 1) The influential variables for childrens'egoistic value orientation were grade level of children and education level of mother The influential variables for childrens'altruistic orientation were the frequency of contact for environmental information and age of mother. The influential variables for childrens'biospheric orientation were education level of mother and the frequency of contact for environmental information. 2) The influential variables for the childrens'behavior on the environmental preservation were the frequency of contact for environmental information. biospheric orientation. grade level of children and education level of mother.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.1032-1037
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• 2006

This thesis studied effects of the excavation around railroads on the deformation of the lateral ground and neighboring railroads. The conclusions of the study are as follows. 1. When the depth of excavationis 10m, the influential area should be 35m for soft clay, 20m for normal clay, 15m for hard clay, 15m for loose sand, 12m for slightly dense sand, and 8m for dense sand. 2. When the influential area is 10m, the allowable excavation depth should be 2.5m for soft clay, 4.8m for normal clay, 7.5m for hard clay, 7.2m for loose sand, 8.8m for slightly dense sand, and 10m for dense sand. 3. When the influential area is 20m, the allowable excavation depth should be 4.5m for soft clay, and up to 10m for the other five kinds of soil. 4. When the influential area is 30m, the allowable excavation depth should be 7.5m for soft clay, and up to 10m for the other five kinds of soil. 5. When the influential area is 35m, the allowable excavation depth should be up to 10m for all kinds of soil.