• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.959-975
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• 2013

The SAS macro faces program by Friendly (1992) is for Chernoff face analysis, which is one of methods for the visualization representation of multivariate data. In this paper, we examined 18 face features used in the program and presented the modified program depending on the definition of a good face in days present. In addition, a good bank evaluation for 15 domestic banks was performed through Chernoff face analysis based on 11 bank economic indicators representing stability, the consumer satisfaction, soundness, and banks profitability.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1201-1208
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• 2006

Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.21-27
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• 2006

Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1207-1216
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• 2015

This study aims to compare the model power in developing corporate credit rating models and to suggest a good way to build models based on the characteristic of data. Among many measurement methods, AR is used to measure the model power under various conditions. SAS/MACRO is in use for similar repetitions to reduce time to build models under several combination of conditions. A corporate credit rating model is composed of two sub-models; a credit scoring model and a default prediction model. We verify that the latter performs better than the former under various conditions. From the result of size comparisons, models of large size corporate are more powerful and more meaningful in financial viewpoint than those of small size corporate. As a corporate size gets smaller, the gap between sub-models becomes huge and the effect of outliers becomes serious.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.675-682
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• 2002

In this study, we develop the statistical analysis program for genetic analysis of diallel crosses data by SAS/MACRO, SAS/IML. Genetic analysis is to estimate of genetics parameters and heredity with reciprocal cross and without reciprocal cross. Statistical analysis program solve the problem of the difficulties on the data analysis in field denetics and breeding Therefore the user whoever want to analysis of data on genetics and breeding easily conduct the work saving time and suffering.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.279-287
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• 2007

Data fusion is the process of combining multiple data in order to produce information of tactical value to the user. Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. In this paper, we develop was macro program for statistical matching which is one of five branch types for data fusion. And then we apply data fusion and association rule techniques to environmental data.

• Korean Journal of Community Nutrition
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• v.19 no.2
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• pp.176-186
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• 2014

Objectives: Epidemiological studies have suggested that a higher consumption of whole grain foods can significantly reduce the risk of chronic diseases including cardiovascular diseases, type 2 diabetes and obesity. The objective of the current study was to examine associations among the consumption of whole grains and nutrient intakes and biochemical indicators associated with chronic diseases among generally healthy middle-aged Korean women. Methods: Using 24-hour recall data from the 2008-2009 National Health and Nutrition Examination Surveys, whole grain intake (g/day) was calculated for a total of generally healthy 1,953 subjects. The subjects were divided into three groups by the level of whole grain consumption (0 g/day, > 0 and < 20 g/day or ${\geq}20g/day$). Mean values or proportions of various nutrient intakes and metabolic risk factors were compared according to the level of whole grain consumption. All statistical analysis was conducted using SAS software version 9.2. Results: We observed that the overall consumption of whole grains was quite low. Specifically, 58.2% of subjects reported no whole grain consumption on the day of the survey, and the mean whole grain intake was only 15.3 g/day. The whole grain consumption was positively associated with intakes of various macro and micronutrients, namely, plant proteins and fats, dietary fiber, calcium, plant iron, potassium, zinc, vitamin A, ${\beta}$-carotene, thiamin, riboflavin, niacin, vitamin $B_6$ and folic acid. In addition, we found significantly decreasing trends in abdominal obesity and hypertriglyceridemia as whole grain intake levels increase. Conclusions: The study findings suggested the importance of promoting whole grain consumption as an efficient tool for improving various dietary aspects and preventing chronic diseases.

• Journal of Nutrition and Health
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• v.57 no.1
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• pp.88-104
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• 2024

Purpose: High-sensitivity C-reactive protein (hs-CRP) is primarily synthesized in the liver upon stimulation of infectious disease cytokines, such as interleukin-6 (IL-6), and is used as a biological marker of systemic inflammation. Previous studies reported that hs-CRP is closely related to diet and abdominal obesity. Furthermore, a dietary score favoring the consumption of vegetables, fruits, and whole grains over meat and saturated fat reduced inflammation and decreased the prevalence of obesity and abdominal obesity. Nevertheless, no studies have examined whether hs-CRP mediates the relationship between dietary scores and abdominal obesity, and research on the Korean Healthy Eating Index (KHEI) is lacking. Therefore, the present study examined the association between the KHEI and abdominal obesity and the mediating effect of hs-CRP. Methods: In total, 17,770 adults aged ≥19 years were included in the study using the Korea National Health and Nutrition Examination Survey 2015-2018. KHEI was developed to assess the overall diet quality of Korean adults. Multivariable linear and logistic regression analyses assessed the relationship between KHEI, hs-CRP, and abdominal obesity. The mediation analysis with the bootstrapping method was performed using SAS MACRO. Results: Among women, the odds ratio (OR) of abdominal obesity prevalence was lower in the highest KHEI compared to the lowest KHEI after adjusting for age, body mass index, educational level, income level, occupational status, marital status, household type, region type, alcohol consumption, smoking status, physical activity, total energy intake, and hsCRP (OR 0.744, 95% confidence interval 0.598-0.926). The association between KHEI and abdominal obesity was partially mediated via hs-CRP, and the mediated proportion was 68.7% in men and 38.1% in women. Conclusion: A substantial relationship was observed between the KHEI and abdominal obesity among females. Moreover, according to the KHEI, abdominal obesity may be mediated partially by hs-CRP.