• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.493-505
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• 1997

The analysis of binary data appears to many areas such as statistics, biometrics and econometrics. In many cases, data are often collected in which some observations are incomplete. Assume that the missing covariates are missing at random and the responses are completely observed. A method to Bayesian analysis of the binary regression model with incomplete data is presented. In particular, the desired marginal posterior moments of regression parameter are obtained using Meterpolis algorithm (Metropolis et al. 1953) within Gibbs sampler (Gelfand and Smith, 1990). Also, we compare logit model with probit model using Bayes factor which is approximated by importance sampling method. One example is presented.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.7
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• pp.831-842
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• 2003

The purpose of this study is to analyze body types of Chinese women and provide concrete information on it by classifying them into several representative groups. As for the method of this study, statistical analysis is made of 79 items. This is done from July 18 to Aug 07, 2002, 525 female subjects from age 20 to 49 participated in this study. They all live in Beijing and Shanghai in China. The results of this study are as follows. 1. Means, standard deviations, the maximum and minimum of 19 items are extracted. The height and girth item have a high standard deviations. 2. 8 factors are extracted by using factor analysis. Factor 1: body obesity, Factor 2: vertical body size, Factor 3: upper body length Factor 4: size of ankles, Factor 5: angle of shoulders, Factor 6: length of hip Factor 7: size of shoulder, Factor 8: shape of chest 3. The body types of Chinese women are classified into 5 sub groups from the result of the Cluster analysis.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.6
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• pp.765-772
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• 2017

Objective: This study examines the genetic factors influencing the phenotypes (four economic traits:oleic acid [C18:1], monounsaturated fatty acids, carcass weight, and marbling score) of Hanwoo. Methods: To enhance the accuracy of the genetic analysis, the study proposes a new statistical model that excludes environmental factors. A statistically adjusted, analysis of covariance model of environmental and genetic factors was developed, and estimated environmental effects (covariate effects of age and effects of calving farms) were excluded from the model. Results: The accuracy was compared before and after adjustment. The accuracy of the best single nucleotide polymorphism (SNP) in C18:1 increased from 60.16% to 74.26%, and that of the two-factor interaction increased from 58.69% to 87.19%. Also, superior SNPs and SNP interactions were identified using the multifactor dimensionality reduction method in Table 1 to 4. Finally, high- and low-risk genotypes were compared based on their mean scores for each trait. Conclusion: The proposed method significantly improved the analysis accuracy and identified superior gene-gene interactions and genotypes for each of the four economic traits of Hanwoo.

• Spatial Information Research
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• v.10 no.2
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• pp.233-246
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• 2002

The purpose of this paper is to quantitatively measure the effect of location in evaluating the land value through the implementation of GIS coupled with spatial statistical analysis. We assumed that the hedonic price model, which was commonly used in modelling the land value, could not explain the spatial factor effectively. In order to add the spatial factor, the analysis of the spatial autocorrelation was used. The present project used 54 standard land price samples from 1421 parcel land values and applied Kriging to predict stochastically the unsampled values on the basis of spatial autocorrelation between location of vector data. This study confirms that the spatial variogram analysis has an advantage of predicting spatial dependence process and revealing the positive premium and the negative penality on location factor objectively.

• Fashion & Textile Research Journal
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• v.15 no.3
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• pp.414-422
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• 2013

This study identifies the foot shapes of elderly men by classifying foot types according to the shapes of sole of foot and analyzing individual characteristics. The subjects were 269 elderly men over 60 years of age. Their right feet were measured indirectly with a 2D scanner. The anthropometric measuring items consisted of 38 items that were estimated on the right foot of each subject. The 2D scan data were analyzed by various statistical methods such as factor analysis, ANOVA and cluster analysis using the statistical program SPSS 19.0. A total of 8 factors were extracted through a factor analysis and these factors represent 77.83% of total variance. The 8 factors were: ball and lateral foot protrusion, ball gradient, medial foot protrusion, anterior and posterior foot length ratio, lateral ball length, heel size, toes breadth, and foot length, that explained 77.83% of the total variance. A total of 4 clusters (as their sole type) were categorized using 8 factor scores by cluster analysis. Type 1 was classified as H-type(toes width, foot width, heel width uniform and medial malleolus and lateral malleolus almost no protrusion). Type 2 was classified as V-type(foot width and toes width, wide and heel width narrow). Type 3 was classified as A-type(foot width and heel width, wide but toes width narrow, protruded inside). Type 4 was classified as D-type(protruded outside).

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.933-942
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• 2013

Common factor analysis and principal component analysis represent two technically distinctive approaches to exploratory factor analysis. Much of the psychometric literature recommends the use of common factor analysis instead of principal component analysis. Nonetheless, factor analysts use principal component analysis more frequently because they believe that principal component analysis could yield (relatively) less accurate estimates of factor loadings compared to common factor analysis but most often produce similar pattern of factor loadings, leading to essentially the same factor interpretations. A simulation study is conducted to evaluate the relative performance of these two approaches in terms of factor pattern recovery under different experimental conditions of sample size, overdetermination, and communality.The results show that principal component analysis performs better in factor recovery with small sample sizes (below 200). It was further shown that this tendency is more prominent when there are a small number of variables per factor. The present results are of practical use for factor analysts in the field of marketing and the social sciences.

• Culinary science and hospitality research
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• v.13 no.4
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• pp.164-177
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• 2007

The purpose of this study is to explore the relationship between the service of employees in the foodservice industry and their customers' satisfaction. The study surveyed 310 subjects who are the employees of companies in Busan, Ulsan, City and Gyeongsangnam-do and processed the result using SPSS for Win V. 12. 0. For statistical analysis, Frequency, Factor Analysis and Regression were put into operation. As a result of Factor Analysis on the quality of company food-service, six factors have been extracted. The result of the Factor Analysis of satisfaction revealed one factor. In conclusion, this study shows that the quality of foodservice - food, convenience, menu, kindness, hygiene/cleanliness, facilities - had a positive effect on users' satisfaction. It is expected that the results will provide a base for marketing strategies to be used by the managers and marketers in foodservice companies.

• Journal of Korean Society for Atmospheric Environment
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• v.6 no.2
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• pp.155-160
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• 1990

During the period from Mar. 1985 to Feb. 1988, airborne particulate matters were collected and size fractionated by the ANdersen high volume air sampler in Seoul. The concentrations of several heavy metals (Pb, Cu, Zn, Fe, Mn) and benzo(a)pyrene were determined to investigate the size distributions and seasonal variations. And with respect to seven components in the total suspended particulate (TSP), the factor analysis was performed for three groups such as the coarse particles (> 2 $\mu$m), fine particles (< $\mu$m) and TSP. As a result of factor analysis by using the varimax method, the chemical components in the TSP were able to characterize with two principal factors. The first factor, F1 was considered to be a factor indicating the contribution of natural sources and the second factor, F2 was a factor indicating the degree of artificial sources. Each components in the TSP was divided into two main groups of components originated from soil and/or road dust and pollutants originated from automobiles and/or human work.

• Physical Therapy Korea
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• v.23 no.1
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• pp.31-37
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• 2016

Background: The assessment tool developed in other countries should be translated into Korean language using rigorous methodological approaches in order to be used in Korea. Because these procedures are insufficient for establishing the cross-cultural and linguistic equivalence, the need for statistical methods is raised. The Fullerton Advanced Balance Scale was translated into Korean and the content validity was verified through the back translation method, but the reliability and validity have not yet been proven by statistical methods. Objects: The purpose of this study was to investigate the reliability and validity of the Korean version of the Fullerton Advanced Balance Scale (KFAB) by statistical methods in elderly people. Methods: A total of 97 elderly adults (39 males and 58 females) participated in this study. Internal consistency of the KFAB was measured using Cronbach's alpha and an intraclass correlation coefficient (ICC) was used to assess test-retest reliability between the two measurement sessions. Concurrent validity was measured by comparing the KFAB responses with the Korean version of the Berg Balance Scale (KBBS) using the Spearman correlation coefficient. Construct validity of the KFAB was measured using the exploratory factor analysis to evaluate the unidimensionality of the questionnaire. The significance level was set at ${\alpha}=.05$. Results: The internal consistency of the KFAB was found be adequate with Cronbach's alpha (.96), and test-retest reliability was excellent as evidenced by the high ICC (r=.996). Concurrent validity showed high correlation between the KFAB and KBBS (r=.89, p<.001). Construct validity was evaluated using exploratory factor analysis. The result from Bartlett test of sphericity was statistically significant (p<.001), and the value of Kaiser-Meyer-Olkin measure of sampling adequacy was .93. Exploratory factor analysis revealed the existence of only one dominant factor that explained 76.43% of the variance. Conclusion: The KFAB is a reliable, valid and appropriate tool for measuring the balance functions in elderly people.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.6
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• pp.631-642
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• 1998

Fall-out particles were collected by the modified British deposit gauges at 35 sampling sites in Suwon area from January to November, 1996. Twenty chemical species (Al. Ba, Cd, Cr, K, Pb, Sb, Zn, Cu, Fe, Ni, V, F-, Cl-, NO3-, 5042-, Na+, NH4+, Mg2+, and Ca2+) were analyzed by AAS and If. The purposes of this study were to estimate qualitatively various emission sources of the fell-out particle by applying multivariate statistical techniques such as factor analysis, multiple regression analysis, and discriminant analysis. During the study, outlier sites were determined by a z-score method. Cl-, Na+, Mg2+, and SO42- were highly correlated due to their common marine related source. Wind speed was the most influential factor for the deposition fluxes of the particle itself and all the chemical species as well. When applying the factor analysis, 8 source patterns were qualitatively obtained, such as marine source, soil source, oil burning source, Cr related source, tire source, Cd related source, agriculture source, and F- related source. As a result of the multiple regression analysis, we could suggest that some chemical compounds may possibly exist in the form of CaSO4, NaN03, NaCl, MgC12, (NH4)2SO4, NaF, and CaCl2 in the fall-out particles. Finally, spatial and seasonal classification study performed by a discriminant analysis showed th.at SO42-, Ca2+, Cl-, and Fe were dominant in the group of spatial pattern; however, SO42-, Cl-, Al, and V were in the group of seasonal pattern.