• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.661-666
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• 2003

In this paper, the conventional k-modes and fuzzy k-modes algorithms for clustering categorical data is extended by representing the clusters of categorical data with fuzzy centroids instead of the hard-type centroids used in the original algorithm. The hard-type centroids of the traditional algorithms had difficulties in dealing with ambiguous boundary data, which might be misclassified and lead to thelocal optima. Use of fuzzy centroids makes it possible to fully exploit the power of fuzzy sets in representing the uncertainty in the classification of categorical data. The distance measure between data and fuzzy centroids is more precise and effective than those of the k-modes and fuzzy k-modes. To test the proposed approach, the proposed algorithm and two conventional algorithms were used to cluster three categorical data sets. The proposed method was found to give markedly better clustering results.

• Journal of Korean Academy of Nursing
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• v.21 no.3
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• pp.307-322
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• 1991

The purpose of this exploratory study was to analyze nursing role conceptions and test the relationships between nursing role conceptions and professional commitment among selected Korean nurses. Data were obtained from a convenience sample of 262 practising nurses of varying positions, education, and experience. The total sample represents a response rate of 93 percent. Subscales of Nursing Role Conceptions (Pieta, 1976) were used to measure professional, service, and bureaucratic role conceptions 1 the tool to measure professional commitment was developed by the investigator. The results of this study were as follows. 1. Professional role conception and service role conception were positively related(normative r＝ .61 : categorical r＝ .64). Bureaucratic role conception scores(32.6$\pm$4.97) were higher than professional and service role conception scores. 2. Experience was positively related to bureaucratic professional categorical role conception(r＝ .17, p＜ .01), and negatively related to bureaucratic professional role discrepancy(r＝- .12, p＜ .01). There was no relationship between experience and service role conception. This study also showed that nurses who had longer experience tended to have higher role conceptions on all three subscales. 3. Nurses with a master's degree had significantly higher professional and bureaucratic role conceptions scores. Bacealaureates graduates had the lowest bureaucratic categorical role conception scores ; associate nurses had the lowest professional categorical role conception scores. 4. Nursing supervisors and head nurses had significantly higher bureaucratic categorical role coneption scores, whereas they had lower bureaucratic normative and professional role conception scores. 5. Age and experience were positively related to professional commitment (r＝ .24, r＝ .28). Hierarchical multiple regression analyses showed that the combination of nursing role conceptions explained greater variance in professional commitment pair of the variables alone. Further research employing dynamic designs is needed to execute rigorous tests of causal models of nursing role conceptions and professional commitment. The findings of this study suggest that antecedents and moderating variables of nursing role conception and professional commitment need to be explored for further theoretical. specification and empirical evaluation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.207-215
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• 1997

This paper deals with a comparison between Taguchi's accumulation analysis method and Nair test on the ordered categorical data from an industrial experiment for quality improvement. a result of Taguchi's accumulation analysis method is shown to have reasonable power for detecting location effects, while Nair test identifies the location and dispersion effects separately, Accordingly, Taguchi's accumulation analysis needs to develop methods for detecting dispersion effects as well as location effects. In addition this paper rewmmends models for analyzing ordered categorical data, for examples, the cumulative legit model, mean response model etc Successively simple, reasonable methods should be introduced more likely to be used by the practitioners.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.371-385
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• 2003

In this paper, contour plot is considered as a method to explore the structure of categorical data. For this purpose, the paper suggests a method to sort two-way contingency table with respect to the expected marginals. It is found that the suggested plot provides us with valuable information for the underlying data structure. Firstly, we can investigate independency between the categories by examining the differences of expected frequency contours and observed frequency contours. With the plot, we can also visually investigate the existence of outliers inherent in the data. These properties of the suggested contour plot will be demonstrated by several sets of real data.

• Journal of Korean Society for Quality Management
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• v.32 no.3
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• pp.109-125
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• 2004

This paper deals with an optimal process control problem in production of hull structural steel plate with high defective rate. The main quality characteristic(dependent variable) is the internal quality(defect) of plates and is dependent on process parameters(independent variables). The dependent variable(quality characteristics) has three categorical ordinal data and there are 35 independent variables(29 continuous variables and 6 categorical variables). In this paper, we determine the main factors and to develop the mathematical model between internal quality predicted probabilities and the main factors. Secondly, we find out the optimal process condition of main factors through analysis of variance(ANOVA) using simulation. We consider three models to obtain the main factors and the optimal process condition: linear, quadratic, error models.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1621-1629
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• 2016

This paper studies Bayesian pooling for analysis of categorical data from small areas. Many surveys consist of categorical data collected on a contingency table in each area. Statistical inference for small areas requires considerable care because the subpopulation sample sizes are usually very small. Typically we use the hierarchical Bayesian model for pooling subpopulation data. However, the customary hierarchical Bayesian models may specify more exchangeability than warranted. We, therefore, investigate the effects of pooling in hierarchical Bayesian modeling for the contingency table from small areas. In specific, this paper focuses on the methods of direct or indirect pooling of categorical data collected on a contingency table in each area through Dirichlet priors. We compare the pooling effects of hierarchical Bayesian models by fitting the simulated data. The analysis is carried out using Markov chain Monte Carlo methods.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.683-692
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• 2010

This short article is concerned with a categorical time series obtained after clipping a heteroscedastic GARCH process. Estimation methods are discussed for the model parameters appearing both in the original process and in the resulting binary time series from a clipping (cf. Zhen and Basawa, 2009). Assuming AR-GARCH model for heteroscedastic time series, three data sets from Korean stock market are analyzed and illustrated with applications to calculating certain probabilities associated with the AR-GARCH process.

• Journal of the Korean Society of Safety
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• v.17 no.1
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• pp.94-98
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• 2002

This study aimed to search for the fundamental accident causes using a categorical analysis, a kind of statistical methods. As the analysis methods, correlation analysis, independence test and logistic regression analysis were used. And the SPSS package, a general-purpose mathematical library, was used to obtain statistical characteristics. As the result of this study, the accident causes associated with factor of 'lost working days' were factors such as 'employed periods', 'sex', 'type of accident', 'month'. In case of applying independence test method, the most important cause was the factor of 'month'. In case that logistic regression analysis method was applied, the cause contributed to the increase structure'. 'less than 6 month'. On the basis of these results, the plan for accident prevention and the proper investment for accident prevention expenditure could be carried out in each workshop.

• Architectural research
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• v.16 no.2
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• pp.75-80
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• 2014

Risks, uncertainties, and associated cost overruns are critical problems for construction projects. Cost contingency is an important funding source for these unforeseen events and is included in the base estimate to help perform financially successful projects. In order to predict more accurate contingency, many empirical models using regression analysis and artificial neural network method have been proposed and showed its viability to minimize prediction errors. However, categorical factors on contingency cannot have been treated and thus considered in these empirical models since those models are able to treat only numerical factors. This paper identified potential factors on contingency in transportation construction projects and evaluated categorical factors using the one-way ANOVA statistical method. Among factors including project work type, delivery method type, contract agreement type, bid award type, letting type, and geographical location, two factors of project work type and contract agreement type were found to be statistically important on allocating cost contingency.

• Korean Journal of Child Studies
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• v.33 no.5
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• pp.19-35
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• 2012

The purposes of this study were to investigate how children's categorization differs in object categorical hierarchy and to examine whether these aspects were different according to the children's age of 18 months, 24 months, 30 months. The participants consisted of 120 young children aged 18 months, 24 months, and 30 months from 31 child-care centers located in middle-income regions of Seoul and Kyonggi Province. The major findings were as follows : First, all the children from all three age groups could consistently differentiate the superordinates; however, they could not consistently differentiate basic categories. Second, 24 month appears to be a critical change period in category development. Third, as the children become older, they are able to acquire more knowledge regarding categories. These results suggested that the advent of ordering, in terms of basic categories as well as superordinates which occurred around the age of 24 month, was confirmed in category development.