• Health Policy and Management
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• v.18 no.1
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• pp.43-62
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• 2008

The purpose of this study is to evaluate the causal relationship among health care criteria in Korean National Mental Hospitals, using Malcolm Baldrige National Quality Award(MBNQA). The survey instrument consists of 92 Questions from the seven the MBNQA health care criteria. Structural Equation Modeling (SEM) is used to analyze the empirical data and estimates the path coefficients among the seven categories. The result of this study indicates that Leadership drives Foundation and Direction, which influence on Systems that creates Results. Conclusively, among 18 hypotheses, 15 are statistically significant.

• Journal of the Korean Home Economics Association
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• v.35 no.5
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• pp.177-194
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• 1997

This study attempts to explore urban married women's needs for consumer information contents. In addition, the causality of the needs for consummer information contents and related variables is investigated. Major findings are the following: (1) Respondents' need for information on“the product selection”and “the use and management”of the washing maching or hair dryer is high, while the in need for the information on“the existing brands”is very low. (2) Among several relevent characteristics, respondents' product involvement is strongly related to the needs for consumer information contents. (3) The results of the analysis of casual model from washing maching showed that respondents' age, purchasing experience, perception of the price dispersion and quality difference, self confidence in the product evaluation affect on the need for consumer information contents directly. While respondents' income and education level show a indirect effect. (4) The results of the analysis of causal model from hair dryer showed that respondents' perception of the price dispersion, quality difference and product complexity affect on the need for consumer information contents directly. While respondents' age, purchasing experience, self-confidence in the product evaluation show a indirect effects.

• International Commerce and Information Review
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• v.10 no.1
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• pp.329-347
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• 2008

The purpose of this study is to examine the causal relationship between the exchange rate and economic growth, and to induce policy implications. In order to test whether time series data is stationary and the model is fitness or not, we put in operation unit root test, cointegration test. And we apply Granger causality based on an error correction model. The results indicate that uni-dierctional causality between exchange rate and economic growth is detected. Exchange rate impacts on economic growth, but economic growth don't impact on exchange rate. The analysis of impulse reaction function shows that the impulse of exchange rate impacts on Korean economic growth in negative direction. We can infer policy suggestion as follows: The fluctuation of exchange rate much affects economic growth, thus we must make a stable policy of exchange rate to continue economic growth.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.65-86
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• 2000

The estimates from an EM when it is applied to a large causal model of 10 or more categorical variables are often subject to the initial values for the estimates. This phenomenon becomes more serious as the model structure becomes more serious as the model structure becomes more complicated involving more variables. In this regard Wu(1983) recommends among others that EMs are implemented several times with different sets of initial values to obtain more appropriate estimates. in this paper a new approach for initial values is proposed. The main idea is that we use initials that are calibrated to data. A simulation result strongly indicates that the calibrated initials give rise to the estimates that are far closer to the true values than the initials that are not calibrated.

• Communications for Statistical Applications and Methods
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• v.27 no.6
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• pp.675-688
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• 2020

In survival analysis of observational data, the inverse probability weighting method and the Cox proportional hazards model are widely used when estimating the causal effects of multiple-valued treatment. In this paper, the two kinds of weights have been examined in the inverse probability weighting method. We explain the reason why the stabilized weight is more appropriate when an inverse probability weighting method using the generalized propensity score is applied. We also emphasize that a marginal hazard ratio and the conditional hazard ratio should be distinguished when defining the hazard ratio as a treatment effect under the Cox proportional hazards model. A simulation study based on real data is conducted to provide concrete numerical evidence.

• The Journal of Korean Academic Society of Nursing Education
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• v.10 no.1
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• pp.54-63
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• 2004

The purpose of this study is to identify the factors that influence stress experienced by nursing students and to provide a perceived causal structure model among these variables. The ultimate goal of this study is to develop efficient guidance to clinical nursing education in this population. This study intends to apply perceived causal structure: network analysis method which was developed by Kelly(1983), and has been applied in nursing research. This method is selected to show dynamic relationship of stressor using network method. Data was collected from convenient sample of 186 junior college nursing students who had the clinical practice experience during 10 weeks. Data collection and analysis was conducted in 2 steps from December, 9, 2002 to February, 8, 2003. Step 1.: Data was collected using literature review(10 articles) to identify the causes of stress. Nine causes of stress were extracted. Step 2.: As perceived casual structure network study, data was collected using questionnaires which included 9 extracted cause and stress. The questionnaire contained a 10 X 10 grid table with 10 causes and effects printed. In network analysis, 'Yes' was scored as 1, 'No' was scored as 0, and the mean(maximum 1, minimum 0) was calculated. Construction of the network under inductive eliminative analysis which stopped the construction of the network when the consensual agreement level dropped near 50% was proceeded by adding causes in order of the mean rating level. In this study, construction of the final network was stopped by consensual agreement level of 52% of the total subjects. The results are summarized as follows : Step 1: Investigation of the causes of stress ; The extracted causes of stress from quality data was identified 9 categories ; negative nurse, lack of clinical practice opportunity, ambiguous role, negative patient, lack of nursing knowledge and skill, difficult of personal relations, inefficient clinical practice guidance, gap of theory and practice, lack of support. Step 2 : Construction of the perceived causal structure model ; 1) The most central cause of stress is ambiguous role in the systems of causation. 2) The distal cause of stress is inefficient clinical practice guidance 3) The causes that have a number of outgoing link are negative nurse, ambiguous role. 4) The causes that have a number of incoming link are ambiguous role, gap of theory- practice, lack of clinical practice opportunity, lack of nursing knowledge- skill. 5) There is a mutual relationship between stress and difficult of personal relations, stress and ambiguous role, ambiguous role and negative nurse, ambiguous role and lack of clinical practice opportunity, ambiguous role and lack of nursing knowledge-skill, lack of nursing knowledge-skill and gap of theory- practice. In conclusion, the network suggests that the first centre cause is related on ambiguous role and the second on negative nurse, inefficient clinical practice guidance in the systems of causation

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.228-231
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• 1998

Artificial Intelligence literatures have recognized that stock market is a highly unstructured and complex domain so that it is difficult to find knowledge that belongs to that domain. This paper demonstrates that the proposed QCOM can derive global knowledge about stock market on the basis of a set of local knowledge and express it as a digraph representation. In addition, inference mechanism using quantitative causal reasoning can describe the qualitative and quantitative effects of exogenous variables on stock market.

• Journal of KIISE:Software and Applications
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• v.28 no.1
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• pp.46-51
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• 2001

2D로 확장한 HMM은 다수 제안되었지만 엄밀한 의미에 있어서 2D HMM이라고 하기에 부족한 점이 많다. 본 논문에서는 기존의 랜덤 필드 모형이 아닌 새로운 2D HMM을 제안한다. 상하 및 좌우 방향의 causal chain 관계를 가정하고 완전한 격자 형성 조건을 두어 2D HMM의 평가, 매개 변수를 추정하는 알고리즘을 제시하였다. 각각의 알고리즘은 동적 프로그래밍과 최우 추정법에 근거한 것이다. 변수 추정 알고리즘은 반복적으로 이루어지며 국소 최적치에 수렴함을 보였다.

• Korean Journal of Adult Nursing
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• v.18 no.1
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• pp.115-124
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• 2006

Purpose: The purpose of this study was to propose a theoretical model of hope commonly held by the cancer patients just after surgery, under the assumptions that hope of those patients is not only realistic and disease oriented but in dialectical circulation. Method: A theoretical model was generated through 4 steps: exploring a hope structure by synthesizing the relevant hope structures expressed in Kim and Tae's studies, in-depth literature review, examining the meanings of the concepts consisted of the structure in use and their causal relations in logical adequacy, proposing a theoretical structure through synthesizing the causal relations, and diagramming the structure. Results: The proposed theoretical model involves concepts such as Cancer Related Uncertainty (CRU), Efforts to Find out the Possibility of Cure or Recovery (EFPCR), and Hopefulness or Hopelessness. The 'EFPCR' is stipulated as 'Behaviors Related to Looking for Evidences or Cues (BRLEC)' and 'Formation of Cognitive Schema (FCS)'. In the model, Hopefulness is directly influenced by 'CRU in low', which is affected by 'FCS in good' from the result of EFPCR started with 'CRU in increase' while 'CRU with increase' from the result from EFPCR has direct effect on Hopelessness. Conclusion: The theoretical model would be used to enhancing hope of the cancer patients in post-operation.

• Management & Information Systems Review
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• v.2
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• pp.267-294
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• 1998

Recently, self-efficacy is one of the critical constructs that have been found to influence human decisions about behavior selection and the performance associated with the selected behavior. The construct has been widely adopted and tested In the fields of social psychology and/or other behavioral sciences. In information systems field, however, it has been hardly studied, although computer self-efficacy could have been an important factor explaining and predicting human computer usage behaviors. From this perspective, main purposes of the study is to understand causal relation among the factors influencing computer self- efficacy, computer usage behavior and computer self-efficacy. The research reported in this study have several objectives; 1) to develop a measure of computer self-efficacy, 2) to Identify the factors influencing self-efficacy, and 3) to reveal the relationship between self-efficacy and computer usage behavior and then 4) to explain the causal model of computer self-efficacy. By reviewing the literature, past experience, others' use, encouragement by others, and anxiety are selected as the factors influencing computer self-efficacy. Four hypotheses concerning the relationship between each of the variables and computer self-efficacy are tested by LISREL. One more hypothesis about the relationship between computer self-efficacy and computer usage is also tested. The results show that computer self-efficacy is significantly influence by computer anxiety, encouragement by others, and computer experience, and that it is closely correlated with computer usage behavior.