• KDI Journal of Economic Policy
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• v.39 no.3
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• pp.43-62
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• 2017

This paper proposes an integrated risk-management framework that includes 1) measuring the risk of credit portfolios, 2) implementing a (macro) stress test, and 3) setting risk limits using the estimated systematic latent factor specific to capture the housing market cycle. To this end, we extract information from a set of real-estate market variables based on the FAVAR methodology proposed by Bernanke, Boivin and Eliasz (2005). Then, we show the method by which the estimated systematic factor is applied to risk management in the housing market in an integrated manner within the Vasicek one-factor credit model. The proposed methodology is well fitted to analyze the risk of slow-moving and low-defaultable forms of capital, such as alternative investments.

• Journal of Korean Society for Quality Management
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• v.28 no.3
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• pp.145-154
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• 2000

Effective management of knowledge is essential to keep up with demands of this challenging information age. The first step for this kind of management would be to define indicators to evaluate the quality of knowledge. In this paper, we use five latent variables (intrinsic quality, representational quality, ease of use of quality, maintainable quality, usage of quality) as basis for a preliminary path analysis for knowledge management. Preliminary study results showed that high intrinsic quality does not necessarily guarantee high frequency of use. A modified questionnaire is made and is used for SERVQUAL. The result of SERVQUAL shows that customers are not relatively happy about both intrinsic quality and its ease of use. Additional path analyses are done for both expected and observed quality indicators. The path model based on the expectation indicated that the presentation method of knowledge would induce its easy maintenance while that based on observation did not back up the same phenomenon.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.151-161
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• 1997

An easy Monte Carlo Gibbs sampling approach is suggested for Bayesian analysis of cumulative logit models for ordinal polytomous data. Because in the cumulative logit model the posterior conditional distributions of parameters are not given in convenient forms for random sample generation, appropriate latent variables are introduced into the model so that in the new model all the conditional distributions are given in very convenient forms for implementation of the Gibbs sampler.

• Journal of Environmental Science International
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• v.3 no.1
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• pp.17-29
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• 1994

An one dimensional atmosphere-vegetation interaction model is developed to discuss of the effect of vegetation on heat flux in mesoscale planetary boundary layer. The canopy model was a coupled system of three balance equations of energy, moisture at ground surface and energy state of canopy with three independent variables of $T_f$(foliage temperature), $T_g$(ground temperature) and $q_g$(ground specific humidity). The model was verified by comparative study with OSUID(Oregon State University One Dimensional Model) proved in HYPEX-MOBHLY experiment. As the result, both vegetation and soil characteristics can be emphasized as an important factor iii the analysis of heat flux in the boundary layer. From the numerical experiments, following heat flux characteristics are clearly founded simulation. The larger shielding factor(vegetation) increase of $T_f$ while decrease $T_g$. because vegetation cut solar radiation to ground. Vegetation, the increase of roughness and resistance, increase of sensible heat flux in foliage while decrease the latent heat flux in the foliage.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.189-196
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• 2000

Conjugate prior density families were motivated by considerations of tractability in implementing the Bayesian paradigm. But we consider problem that the conjugate prior p($\Theta$) cannot be used in restriction of the parameter $\Theta$. This article considers the nonconjugate prior problem of hierarchical Poisson model. We demonstrate the use of latent variables for sampling non-standard densities which arise in the context of the Bayesian analysis of non-conjugate by using a Gibbs sampler.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.203-221
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• 2011

The purpose of this study is to investigate the applications of Structural Equation Modeling(SEM) into MIS area in recent years. Two methodologies, Lisrel and PLS, are adopted for the method comparison. A research model, based upon TAM(Technology Acceptance Model) is used for the analysis of the data set of a previous study. The research model includes six research variables that are composed of twenty-eight question items. 272 data are used for data analyses through Lisrel v.8.72 and Visual PLS v.1.04. This study shows the statistical results of Lisrel are the same to those of PLS. The contribution of this study can be suggested as the followings; (1) A theoretical comparison of two methodologies is shown, (2) A statistical analysis is done at a real-situated data set, and (3) Several implications are suggested.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.407-420
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• 1998

This paper is concerned with selecting covariates to be included in building linear random effects models designed to analyze clustered response normal data. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting premising subsets of covariates. The approach reformulates the linear random effects model in a hierarchical normal and point mass mixture model by introducing a set of latent variables that will be used to identify subset choices. The hierarchical model is flexible to easily accommodate sign constraints in the number of regression coefficients. Utilizing Gibbs sampler, the appropriate posterior probability of each subset of covariates is obtained. Thus, In this procedure, the most promising subset of covariates can be identified as that with highest posterior probability. The procedure is illustrated through a simulation study.

• Journal of Korean Public Health Nursing
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• v.28 no.2
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• pp.285-297
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• 2014

Purpose: The purpose of this study was to investigate the structural relationship among the life stress, depression, suicidal ideation of adolescent. Methods: Participants for this study included 285 students from five middle schools located in Seoul and Gyeongsangbukdo, Korea. The SPSS 18.0 program and AMOS 18.0 program were used for analysis of data. Results: The characteristics of this study were to analyze causal relationship with latent variables by considering measurement error and to grasp direct effect, indirect effect and total effect. Life stress and depression were found to be factors influencing suicidal ideation. Depression was a direct factor and life stress was a indirect factor. The effects of depression as a mediator between life stress and suicidal ideation were significant statistically. Conclusion: The findings of this study may provide useful assistance in development of effective nursing interventions for prevention and management of middle school students' suicidal ideation.

• Korean Journal of Child Studies
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• v.28 no.4
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• pp.73-95
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• 2007

Causal relationships of kindergarteners' phonological awareness and processing to their ability to read words was investigated with the participation of 289 4- to 6-year-old children attending three kindergartens in Busan. Results showed gradual growth in reading ability with age. Children performed best in reading words and poorest in reading low frequency letters. They showed continuous development in skills of syllable deletion, phoneme substitution, phoneme insertion, phonological memory and naming. Discontinuous development was found in counting syllables. Longer syllables were difficult to count, and middle syllables of 3 syllable words were hard to delete. Children had poor perception of final consonants of Consonant-Vowel-Consonant syllables. Children's phonological awareness and processing were latent variables strongly related to ability to read words written in Hangul.

• International Journal of Quality Innovation
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• v.6 no.3
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• pp.19-37
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• 2005

It is generally accepted that leadership is the foundation for creation of a company's business results. However, empirical evidence is lacking. This paper examines the relationship between leadership and key performance results based on a Return on Leadership Model. The model links Denison's four leadership traits to people results, customer results, and ultimately key performance results. Further specified, the model is a structural equation model with nine latent variables, each measured by a set of indicators, observed by survey questions. To validate the model, an empirical study was conducted, and 379 managers from medium-sized and large companies in Denmark participated. The estimation of the model shows that the model structure explains return on leadership very well, and the findings support the developed model. We are able to quantify the relationships from leadership to people results, customer results and key performance results and, in this way, the data presented here provide evidence that leadership is linked to key performance results. Several results and applications of the model are shown. The findings provide new knowledge about how leadership can be linked to performance, and how excellent leadership creates key performance results.