• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.6
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• pp.641-652
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• 2012

This study took the conceptual framework of acculturation styles into the empirical investigation of international students in Korea. This research identifies the differences in acculturation styles, the characteristics of each segment, the effect of acculturation styles on clothing involvement (clothing involvement and risk probability), and the effect of cultural orientation values (individualism and collectivism) as covariates. The participants were international students attending a university located in Seoul. Data from 153 international students were used for statistical analysis. Respondents were grouped into four acculturation styles (integration, assimilation, separation, and marginalization). The assimilation group had the highest mean score of clothing interest. Cultural orientation values showed a significant covariate effect. With individualism as covariates, the main effect of acculturation styles on clothing interest was significant. In clothing product evaluation criteria, the integration group regarded design, fit and trend as most important. The marginalization group showed a mean score that was significantly lower in brand preference and satisfaction; however, the assimilation group had a mean score that was significantly higher.

• Journal of the Korean Data and Information Science Society
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• v.4
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• pp.1-11
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• 1993

The Cox's regression model is frequently used for covariate effects in survival data analysis, But, much of the statistical work has focused on asymptotic behavior so the small sample evaluation has been neglected. In this paper, we compare the small or moderate sample performances of the survival function estimators for the Cox's regression model using bootstrap method. The smoothed PL type estimator and the Link estimator are slightly better than corresponding the PL type estimator and the Nelson type estimator in the sense of the achieved error rates.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.149-158
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• 1998

In this paper we suggest the joint model of death times and counts with covariates. We assume that the death times follow a Weibull distribution with rate that depends on covariates. For the counts, a Poisson process is assumed with the intensity depending on time and the covariates. We obtain the maximum likelihood estimators of model parameters. This model is applied to data set of patients with breast cancer who received a bone marrow transplant.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.40-43
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• 2000

In this paper, we investigate how the average survival time of listed companies in the Korea Stock Exchange (KSE) are affected by changes in macro-economic environment and covariate vectors which show peculiar financial characteristics of each company. We also apply the survival analysis approach to the dichotomous firm failure prediction and the results show a similar pattern of forecasting performance using the existing dichotomous prediction techniques. These findings suggest that, when we consider a bankruptcy model under a certain economic event, the survival approach can be a useful alternative to the existing dichotomous prediction methods since the approach provides estimation of average survival time as well as simple binary prediction.

• Journal of Preventive Medicine and Public Health
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• v.31 no.1 s.60
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• pp.72-81
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• 1998

The purpose of this study was to investigate the relation between health behavior patterns and demographic, socio-economic characteristics, health status, health information in Korea. The quantification method through canonical correlation analysis was conducted to the data from Korea National Health Survey in 1995, which consisted of 5,805 persons. The health lifestyle patterns were quantified as good diet lifestyle, passive lifestyle to the negative direction and drinker lifestyle, smoker lifestyle, hedonic lifestyle and fitness lifestyle to the positive direction. The covariate were related to health lifestyle patterns in the order of sex, age, marital status, occupation, health information, economic status, level of physical labour and health status. Characteristics of male, age below 50, married, blue colored worker, no health information, low in economic status, heavy level of physical labour, and poor in health status were positively related to drinker lifestyle, smoker lifestyle, hedonic lifestyle, fitness lifestyle sequentially.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.263-271
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• 2013

This study presents a fuzzy varying coefficient regression model after deleting the outliers to improve the feasibility and effectiveness of the fuzzy regression model. The objective of our methodology is to allow the fuzzy regression coefficients to vary with a covariate, and simultaneously avoid the impact of data contaminated by outliers. In this paper, fuzzy regression coefficients are represented by Gaussian fuzzy numbers. We also formulate suitable goodness of fit to evaluate the performance of the proposed methodology. An example is given to demonstrate the effectiveness of our methodology.

• Environmental Analysis Health and Toxicology
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• v.18 no.1
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• pp.1-13
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• 2003

To estimate the annual WTP for risk reduction of environmental problems such as outdoor and indoor air pollution, and drinking water contamination, a questionnaire survey was conducted by dichotomous contingent valuation method in Seoul. Several covariate models based on Turnbull, Weibull and Spike models were developed and applied to WTP estimation with uncertainty analysis. WTP estimates for risk reduction of air pollution were 13,000 won, 12,000 won, and 10,000 won per month in low-bounded Turnbull, Weibull and Spike models, respectively. The estimates for indoor air pollution were 17,000 won,20,000 won and 21,000 won and these for drinking water contamination were 10,000 won, 13,000 won and 14,000 won in each model, respectively. Goodness of fit for Weibull model was better than those for other models. WTP estimates for indoor air pollution were higher than those for other pollution problems.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.179-182
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• 2003

This study describes a new graphical method for assessing and characterizing effect modification by a matching covariate in matched case-control studies. This method to understand effect modification is based on a semiparametric model using a varying coefficient model. The method allows for nonparametric relationships between effect modification and other covariates, or can be useful in suggesting parametric models. This method can be applied to examining effect modification by any ordered categorical or continuous covariates for which cases have been matched with controls. The method applies to effect modification when causality might be reasonably assumed. An example from veterinary medicine is used to demonstrate our approach. The simulation results show that this method, when based on linear, quadratic and nonparametric effect modification, can be more powerful than both a parametric multiplicative model fit and a fully nonparametric generalized additive model fit.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.415-422
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• 2012

For statistical microarray data analysis, clustering analysis is a useful exploratory technique and offers the promise of simultaneously studying the variation of many genes. However, most of the proposed clustering methods are not rigorously solved for a time-course microarray data cluster and for a fitting time covariate; therefore, a statistical method is needed to form a cluster and represent a linear trend of each cluster for each gene. In this research, we developed a modified hierarchical mixture of an experts model to suggest clustering data and characterize each cluster using a linear mixed effect model. The feasibility of the proposed method is illustrated by an application to the human fibroblast data suggested by Iyer et al. (1999).

• International Journal of Human Ecology
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• v.8 no.1
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• pp.9-18
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• 2007

This study focuses on the relationship between ethnic identity of Asian-Americans and their appreciation of their ethnic body features, based on reference group theory. A convenience sample of 60 male and 52 female students from various Asian ethnicities attending a mid-western university was used for the study. A 2 (gender) by 2 (ethnic identification) by 2 (socializing group) analysis of covariance (ANCOVA) on body image satisfaction as dependent variable and Body Mass Index score as a covariate was conducted. A significant main effect of ethnic identification was found, which indicates the more respondents identified with their ethnic group, the more likely they were to be satisfied with their appearance. The social group affiliation main effect was not significant. The impact of ethnic identification was significant only for those respondents who socialize more with Americans than with Asians. The results support the idea that one's ethnic group functions as a reference group, which influences body image appraisals.