• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.297-306
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• 2004

It is usual that multivariate data analysis produces related (small number of) artificial variates for data reduction. Among them, refer to MDS(multidimensional scaling), MDPREF(multidimensional preference analysis), CDA(canonical discriminant analysis), CCA(canonical correlation analysis) and FA(factor analysis). Varimax rotation of artificial variables which is originally invented in FA for easy interpretations is applied to diverse multivariate techniques mentioned above. Real data analysisis is performed in order to manifest that rotation improves interpretations of artificial variables.

• Korean Journal of Veterinary Research
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• v.53 no.1
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• pp.7-10
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• 2013

A study was conducted to determine the interdependence among the conformation traits of 28 "Pallaresa" cows using principal component analysis. Originally 21 body linear measurements were obtained, from which eight traits are subsequently eliminated. From the principal components analysis, with raw varimax rotation of the transformation matrix, two principal components were extracted, which accounted for 65.8% of the total variance. The first principal component alone explained 51.6% of the variation, and tended to describe general size, while the second principal component had its loadings for back-sternal diameter. The two extracted principal components, which are traits related to dorsal heights and back-sternal diameter, could be considered in selection programs.

• Journal of muscle and joint health
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• v.4 no.2
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• pp.238-248
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• 1997

This study was conducted to identify the characteristics of uncertainty in patients having rheumatoid arthritis. Subjects of the study constituted 528 patients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. A self report questionnaire was used to measure the uncertainty. Reliability coefficients of this instrument was found Cronbach's ${\alpha}=.84$. In data analysis, SPSS PC 6.0 computer program was utilized for descriptive statistics and factor analysis. Three factors were appointed on the basis of literature review for the principal component factor analysis method and Varimax Orthogonal Rotation. The results of factor analysis were as follows ; 1) Three factors for uncertainty were identified through the principal component analysis and varimax rotation, and these contributed 37.4% of the valiance in the total score. Twenty six items among the whole items in the scale loaded above .39 on one of 3 factors. 2) The naming of each factor was as follows : Factor 1 was 'ambiguity' and has 12 items, factor 2 was 'lack of information' and has 8 items, factor 3 was 'unpredictability' and has 7 items. 3) Cronbach's alpha for internal consistency was .84 for the total items and .81, .80, .50 for each of three subscales in that order.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.10b
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• pp.272-273
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• 2005

• Journal of Korean Academy of Nursing
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• v.28 no.2
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• pp.244-255
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• 1998

The purpose of this study was to verify the reliability and validity of the Rosenbaum self-control schedule (SCS) for assessing resourcefulness in Korea and to explore the simplified scale. The study subjects consisted of 787 adults in a community. The data was collected during the period from Oct. to Dec., 1995 and analyzed as Cronbach α, item correlation with total, Pearson correlation and factor analysis with varimax rotation using SAS. Results were as follows : The mean SCS score for this sample was 17.2 and there were statistical differences for gender(men, 13.1 ; women, 20.0) on the SCS scores. The cronbachα of SCS with 36 items was .74 and when simplified with 30 items, it's coefficient alpha was .78. The translated content of the SCS was validated by two nursing faculty members and one professor of psychology. Factor analysis revealed the most parsimonious structure was obtained when six factors were extracted and subsequently rotated via the varimax criterion. There was 40.2% of total communality variance in the SCS with 36 items. The total communality variance was slightly increased to 43.4% with 30 items of the SCS. In order to reduce from 36 items to 30 items, the process excepted 6 items having low item correlation with total and low MSA(means of sampling adequacy) of factor analysis. According to factor analysis, there are six factors such as emotion control, impulse control, self-efficacy, coping with problems, pain control and satisfaction control, The SCS was found to have low, but statistically significant, correlations with social desirability and helplessness. From the above results, it can be concluded that the reliability of the SCS(inherent and simplified) was a acceptable level and its validity was reasonable when comparing it with other validity studies. To determine the usefulness the simplified scale, further study is necessary to simultaneously compare and analyze both scales for stability.

• Journal of Korean Academy of Nursing
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• v.25 no.1
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• pp.141-155
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• 1995

The objective of this study was to develop a scale to measure stress in infertile couples and to test its reliability and validity. Prior to item generation, a basic decision was made to conceptualize stress in infertile couples as including two dimensions and four subdimensions. The dimensions were, intrapersonal stress including cognitive and affective stress, and interpersonal stress including marital and social stress. Initially 95 items were generated from the inter-view data of 31 primary or secondary infertile women and from a literature review. These items were analyzed through the Index of Content Validity(CVI) and 69 items were selected which met 70% or more of the CVI. This preliminary Infertility Stress Scale were analyzed for reliability and construct validity. Item analysis and factor analysis were applied for construct validity. Forty items were selected through item analysis. This procedure was based on the inter-item correlation matrix, a corrected average inter-item correlation coefficient(.30~.70), a corrected item to total correlation coefficient (.03 or more) and information about the alpha estimate if this item was dropped from the scale. The result of the initial factor analysis including varimax rotation produced eight factors. Five items deleted because of factor complexity(indiscriminate factor loadings). The secondary factor analysis including varimax rotation produced seven factors that coincided with the conceptual framework posed for the scale developed. The seven factors were labeled as ‘meaning of children’,‘worthiness’,‘tenacious linking’,‘marital satisfaction’,‘sexual satisfaction’,‘familial adjustment’ and ‘social adjustment’. The alpha coefficient relating to internal consistency was .93 for reliability The results of this study suggest that the measurement derived from the Infertility Stress Scale is useful in assessing the stress of infertile couples.

• Journal of Korean Society of Transportation
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• v.6 no.2
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• pp.35-48
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• 1988

Amongst various analytic methods of internal structure of city, the factor analysis method which uses O-D matrix data has some merits and characteristics compared to other methods. 1) It is possible to find one certain interaction and flow pattern between traffic zones with in a city through reanalyzing O-D data which is too complex to grasp specific meaning or pattern of flow systems. 2) It can be easily visualized the traffic flow pattern by using adequate graphic techniques, and also can clarify the functional areas whose interaction linkages are significantly strong enough between each other. In this study, the taxi traffic O-D data between 42 traffic zones in Kwang-ju city was reanalyzied by varimax rotated factor analysis methods. As a result, four factors that have significant level factor loading (over 0.5 ) and factor score (over 1.0) were sorted out. so to speak four different functional areas were clarified in Kwang-ju city, of the West, the East, the south, and the North functional areas whose interaction linkages are significantly strong enough between each other. In the study, the taxi traffic O-D data between 42 traffic zones in Kwang-ju city was reanalyzied by varimax rotated factor analysis methods. As a result, four factors that have significant level factor loading (over 0.5) and factor score 9over 1.0) were sorted out. so to speak four different functional areas were clarified in Kwang-ju city, of the West, the East, the South, and the North functional area, then these four functional areas are almost coincided with citizen's general conception of community division and administrative district. Accordingly the factor analysis methods using traffic data seems to proved to be very accurate and useful analytic instruments for analyzing flow pattern and clarifying functional areas of city, and believed to provide basic informations and criteria for practical urban land use planning and transportation planning.

• Journal of Digital Convergence
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• v.18 no.5
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• pp.337-345
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• 2020

The purpose of this study was to examine the validity and reliability of the Korean Version of Self-Efficacy Questionnaire (KSE-12), which is used to examine Communication Self-Efficacys for 155 nursing students. To verify the construction factor of the tool, exploratory factor analysis with varimax rotation was performed, resulting in one factors with 12 items. KSE-12 was significantly correlation with GICC (p<.001), and criterion validity was verified. Cronbach's α was .98, showing internal consistency. Therefore, we suggest that it will be useful for the accumulating the evidence data for development of the communication self-efficacy program by using the KSE-12.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.139-144
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• 2011

This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.

• Journal of the Society of Disaster Information
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• v.10 no.3
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• pp.408-418
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• 2014

This study is to clarify the effect of security majoring students' loyalty on department to future direction and job choice to suggest basic data for supporting student to prepare more active school life and future. The research object is security majoring male/female students among Y university in Gyeonggi-do Y city, K university in Gyeongsangbuk-do G city, k university in Gyeonggi-do S city between 1 Fab 2012 to 20 Aug 2012 and we randomly extracted the sample. In this research, we performed exploratory factor analysis and used principal components analysis and selected varimax direct rotation method to prove the reasonability of the contents. We then use the Cronbach's ${\alpha}$ value to measure the trust coefficient and during the process, the repeated or questions lack of correlation were deleted with judgment of researcher to improve trusty and reasonability.