• Journal of Families and Better Life
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• v.16 no.4
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• pp.155-166
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• 1998

The purpose of this study was to develop ' the Behavior Problem Scale for Children and Adolescence' The 518 subjects were selected from 5th and 6th grades of elementary schools and first and second grades of middle schools in Pusan. Statistics used for data analysis were χ2 cramer's V, factor analysis multi-regression Pearson's r, Cronbach's a. The major finding of this study were as follows 1) 80 items of the 159 item scale were acceptable through item discriminant method The discriminant coefficients of the items(Cramer's V) ranged from .48 to .81. 2) 6 factors(shyness aggression hyperactivity withdrawal anxious immature) extracted from factor analysis,. Multi-regression analysis conducted to reduce the length of scale have drawn 42 items for 'the Behavior Problem Scale Children and Adolescence' 3) Reliability coefficients(Cronbach's a) of this scale was 94.

• Journal of the Korean Home Economics Association
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• v.34 no.5
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• pp.1-12
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• 1996

The purpose of this study was to develop the Self-Esteem Inventory for Children in Korea. The 772 subjects were selected from 3rd-6th grades of elementory schools and the first and second grades of middle schools in Pusan. Statistics used for data analysis were Pearson's r, Cramer's V, X2, factor analysis, multi-regression, splithalf reliability, Cronbach's α. The major findings were that 1) eight factors(home self, personality self, academic self, teacher-related self, general self, physical-appearance self, peer-related self, physical-competence self) were extracted by factor analysis, multi-regression analysis conducted to reduce the iength of inventory have drawed 38 items for the Self-Esteem Inventory for Children in Korea. 2) the discriminant coefficients of the items (Cramer's V) ranged from 0.55 to 0.67. 3) the reliability coefficients of this inventory (Cronbach's α) ranged from 0.63 to 0.81. It was concluded that Self-Esteem Inventory for children is acceptable.

• Journal of Korean Academy of Nursing
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• v.43 no.1
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• pp.102-113
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• 2013

Purpose: This study was done to investigate the level of transcultural self-efficacy (TSE) and related factors and educational needs for cultural competence in nursing (CCN) of Korean hospital nurses. Methods: A self-assessment instrument was used to measure TSE and educational needs for CCN. Questionnaires were completed by 285 nurses working in four Korean hospitals. Descriptive statistics, t-test, ANOVA, Pearson correlation coefficients, and multiple regression were used to analyze the data. Results: Mean TSE score for all items was 4.54 and score for mean CCN educational needs, 5.77. Nurses with master's degrees or higher had significantly higher levels of TSE than nurses with bachelor's degrees. TSE positively correlated with English language proficiency, degrees of interest in multi-culture, degree of experience in caring for multi-cultural clients, and educational needs for CCN. The regression model explained 28% of TSE. Factors affecting TSE were degree of interest in multi-culture, degree of experience in caring for multi-cultural clients, and educational needs for CCN. Conclusion: The results of the study indicate a need for nurse educators to support nurses to strengthen TSE and provide educational program for TSE to provide nurses with strategies for raising interests in cultural diversity and successful experiences of cultural congruent care.

• Journal of Korean society of Dental Hygiene
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• v.16 no.5
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• pp.669-676
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• 2016

Objectives: The purpose of the study was to investigate the related factors of scaling experience of multi-cultural adolescents in Korea. Methods: The subjects were 698 multi-cultural adolescents from web-based survey of the 11th(2015) Korean Youth Risk Behavior. Multi-cultural adolescents are defined as the children of marriage migrant women. The study instruments included demographical characteristics of the subjects, oral health behaviors, daily tooth brushing times, health behaviors, and experience of smoking and alcohol consumption. Data were analyzed using PASW statistics 18.0. Results: The experience rate of scaling was 18.8%. Multiple logistic regression analysis revealed that experience of scaling were related with experiences of sealant and fruit consumption. Conclusions: It is very important to provide the continuing oral health prevention program for the adolescents and investigate the cost-benefit effectiveness of oral health care program.

• Knowledge Management Research
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• v.17 no.3
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• pp.45-64
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• 2016

As the digital retail environement becomes prevalent, consumers are given greater opportunities to make purchases across physical and digital boundaries. Prior research emphasizes that the attractiveness of the digital or online channel is relatively determined by spatial specifics of physical locations. The overall market trend combined with prior research suggests that understanding spatial specifics becomes a key to managing both offline and online sales performance together. In this study, we focus on geographic variation in sales performance through offline and online channels and aim to investigate the channel-level sales difference between central and subsidiary areas. To this end, we obtain sales data of skincare and makeup products from a leading cosmetic company. Next, we examine spatial autocorrelations in data and then employ the spatial error models to study the effects of spatial specifics. The empirical findings are as follows. First, there are significant differences in category-specific and channel-level sales between central and subsidiary areas. Second, Moran's I statistics demonstrate the spatial autocorrelations of each variable. Third, spatial error models outperform simple regression models with lower AIC values. Finally, spatial specifics play a greater role in understanding online sales in subsidiary areas whereas they exert greater influence on offline sales in central areas. We believe our study advances the related theory and knowledge of multi-channel retailing and also contributes practically to location-dependent multi-channel strategies and sales data analytics.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.499-510
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• 2016

It is very important to select relevant variables in regression models for survival analysis. In this paper, we introduce a penalized variable-selection procedure in multi-level frailty models based on the "frailtyHL" R package (Ha et al., 2012). Here, the estimation procedure of models is based on the penalized hierarchical likelihood, and three penalty functions (LASSO, SCAD and HL) are considered. The proposed methods are illustrated with multi-country/multi-center bladder cancer survival data from the EORTC in Belgium. We compare the results of three variable-selection methods and discuss their advantages and disadvantages. In particular, the results of data analysis showed that the SCAD and HL methods select well important variables than in the LASSO method.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.129-148
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• 2007

Frailty estimates from the proportional hazards frailty model often lead us to conjecture the heterogeneity in frailty such that the variance of the frailty varies over different covariate groups (e.g. male group versus female group). For such systematic heterogeneity in frailty, we consider a regression model for the variance components in the proportional hazards frailty model, denoted by the MLFM. However, in many cases, the observed data do not show any statistically significant preference between the homogeneous frailty model and the heterogeneous frailty model. In this paper, we propose a Bayesian model averaging procedure with the reversible jump Markov chain Monte Carlo which selects the appropriate model automatically. The resulting regression coefficient estimate ignores the model uncertainty from the frailty distribution in view of Bayesian model averaging (Hoeting et al., 1999). Finally, the proposed model and the estimation procedure are illustrated through the analysis of the kidney infection data in McGilchrist and Aisbett (1991) and a simulation study is implemented.

• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.137-146
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• 2015

Singh (2013) considered the dual problem to the calibration of design weights to obtain a new generalized linear regression estimator (GREG) for the finite population total. In this work, we have made an attempt to suggest a way to use the dual calibration of the design weights in case of multi-auxiliary variables; in other words, we have made an attempt to give an answer to the concern in Remark 2 of Singh (2013) work. The same idea is also used to generalize the GREG estimator proposed by Deville and S$\ddot{a}$rndal (1992). It is not an easy task to find the optimum values of the parameters appear in our approach; therefore, few suggestions are mentioned to select values for such parameters based on a random sample. Based on real data set and under simple random sampling without replacement design, our approach is compared with other approaches mentioned in this paper and for different sample sizes. Simulation results show that all estimators have negligible relative bias, and the multivariate case of Singh (2013) estimator is more efficient than other estimators.

• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.659-669
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• 2021

Multivariate regression often appears in longitudinal or functional data analysis. Since multivariate regression involves multi-dimensional response variables, it is more strongly affected by the so-called curse of dimension that univariate regression. To overcome this issue, Yoo (2018) and Yoo (2019a) proposed three model-based response dimension reduction methodologies. According to various numerical studies in Yoo (2019a), the default method suggested in Yoo (2019a) is least sensitive to the simulated models, but it is not the best one. To release this issue, the paper proposes an selection algorithm by comparing the other two methods with the default one. This approach is called principal selected response reduction. Various simulation studies show that the proposed method provides more accurate estimation results than the default one by Yoo (2019a), and it confirms practical and empirical usefulness of the propose method over the default one by Yoo (2019a).

• Journal of the Korean Home Economics Association
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• v.45 no.1
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• pp.51-61
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• 2007

The purpose of this study was to examine if multi-shop's store image affects store loyalty and brand switching. Two hundred fifty females and males who have purchased fashion products in multi-shop participated in this survey. For data analysis, descriptive statistics, factor analysis, Pearson's correlation and regression analysis were used for this study. The results were as followed. First, respondents' the most favorite multi-shop was MUE, followed by Boon the shop and ABC mart. Second, store image was classified into four factors such as store atmosphere, service of store, store recognition and product variety. Store loyalty was classified into five factors such as emotional relationship, pursue of novelty, trust about salesperson, satisfaction about service, and active loyalty. Third, result revealed that 'product variety' and 'store atmosphere', 'store recognition', 'service of store' accounted for 39.6% of the explained varience in store loyalty, and 'store recognition' accounted for 4% of the explained varience in brand switching behavior, while 'trust about salesperson', 'pursue of novelty' accounted for 5% of the explained varience in brand switching behavior. Based on these results, multi-shop's fashion marketing strategy would be suggested.