• 응용통계연구
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• 제30권5호
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• pp.615-632
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• 2017

무작위 통제시험에서와 달리, 관찰연구에서는 편향되지 않은 인과관계를 추론하기 위한 통계적 전략이 필요하다. 최근 잠재범주분석(latent class analysis; LCA)에서 처치의 평균인과효과(average causal effect; ACE)를 추정하기 위한 새로운 방법들이 제안되었으나 이러한 방법들은 실제 데이터를 분석하는 응용 연구에 초점이 맞춰있다. 따라서 ACE의 참값을 알 수 없어 추정 방법의 성능을 평가하는 데 한계가 있다. 본 연구에서는 Park과 Chung(2014)이 제안한 방법을 개선하여, 다항범주형 처치변수가 잠재변수인 상황에서 다항범주형 결과변수에 미치는 인과효과 추정방법을 제안하고 처치변수와 결과변수가 잠재변수 또는 관측변수를 포함하는 여러 상황에서 본 연구가 제안한 인과효과 추정방법의 성능을 모의실험연구를 통하여 평가하고자 한다. 더불어 'National Longitudinal Study of Adolescents Health'자료를 사용하여 미국 여성 청소년 성장과 약물사용에 대한 인과효과를 추론하고자 한다.

• 대한인간공학회지
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• 제30권1호
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• pp.137-150
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• 2011

Nationally and internationally reported statistics on marine accidents show that 80% or more of all marine accidents are caused fully or in part by human error. According to the statistics of marine accident causes from Korean Maritime Safety Tribunal(KMST), operating errors are implicated in 78.7% of all marine accidents that occurred from 2002 to 2006. In the case of the collision accidents, about 95% of all collision accidents are caused by operating errors, and those human error related collision accidents are mostly caused by failure of maintaining proper lookout and breach of the regulations for preventing collision. One way of reducing the probability of occurrence of the human error related marine accidents effectively is by investigating and understanding the role of the human elements in accident causation. In this paper, causal factors/root causes classification systems for marine accident investigation were reviewed and some typical human error analysis methods used in shipping industry were described in detail. This paper also proposed a human error analysis method that contains a cognitive process model, a human error analysis technique(Maritime HFACS) and a marine accident causal chains, and then its application to the actual marine accident was provided as a case study in order to demonstrate the framework of the method.

• 대한인간공학회지
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• 제20권3호
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• pp.47-60
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• 2001

The purpose of this paper is propose an analytical method for evaluating user satisfaction of Internet website and identifying casual relationships between user satisfaction of Internet website and performance measures as like revisit intention and complaints using the structural equation model (SEM). This paper is intended to identify critical evaluation factors of user satisfaction for Internet website to determine criteria for evaluating the website. and use the criteria to develop a SEM model for quantitatively evaluation of each factors effects of user preference. The SEM model used 5 latent variables for the evaluation factors of website user satisfaction and 2 latent variables for performance evaluation. 2 portal sites were evaluated to construct the SEM model. and 74 subjects participated the website evaluation using the walk-through and face-to face survey method. Analysis results showed that the SEM model was statistically significant for all the 2 websites evaluated.

• 한국산업정보학회논문지
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• 제8권2호
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• pp.72-83
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• 2003

본 논문은 기존 연구에서 제시된 교육리더쉽, 과정개선, 교육환경, 지역참여, 학생성과 및 교육품질 만족 등의 교육품질요인들 간의 인과관계를 경로분석을 이용하여 분석하였다. 본 논문에서는 교육품질요인들을 몇개의 측정변인으로 측정하고 SEM(구조방정식모형) 분야에서 가장 효율적인 AMOS를 이용하여 분석하였다. 교육 품질요인간의 인과관계분석을 위해서 본 논문에서는 위에서 제시한 요인들로 구조방적식모형을 설계하였다. 분석결과, 교육품질요인들 간에는 뚜렷한 인과관계가 나타났다. 특히 교육리더쉽이 중요한 원인변인이었으며 이것이 교육성과에 영향을 주고 나아가서 교육품질에 영향을 주는 전형적인 한국교육현상을 반영하고 있었다.

• 한국정보전자통신기술학회논문지
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• 제11권2호
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• pp.169-174
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• 2018

일반적으로 자료의 효과 연속형인 경우 분산분석과 이산형인 경우 분할표 카이제곱 검정을 통계적 분석방법으로 사용한다. 다차원의 자료에서는 계층적 구조의 분석이 요구되어지며 자료간의 인과관계를 나타내기 위해 통계적 선형모형을 채택하여 분석한다. 선형모형의 구조에서는 자료의 정규성이 요구되어지며 일부 자료에서는 비 선형모형을 채택할 수도 있다. 특히, 설문조사 자료 구조는 문항의 특성상 이산형 자료의 형태가 많아 모형의 조건에 만족하지 않는 경우가 종종 발생한다. 자료구조의 차원이 높아질수록 인과관계, 교호작용, 연관성분석 등에 다차원 범주형 자료 분석 방법을 사용한다. 본 논문에서는 확률분포의 계산을 이용한 베이지안 네트워크 모형이 범주형 자료 분석에서 분석절차를 줄이고 교호작용 및 인과관계를 분석할 수 있다는 것을 제시하였다.

• 한국지구과학회지
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• 제30권1호
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• pp.111-126
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• 2009

본 연구의 목적은 판의 경계에 대한 그리기와 면담의 결과를 바탕으로 정신모형의 유형별 분석 준거를 도출하고 이를 근거로 고등학생들의 정신모형을 밝히는데 있다. 이를 위하여 고등학교 2학년 학생을 대상으로 충돌형, 섭입형, 발산형 판의 경계에 대한 그리기 과제와 개별 면담을 병행하여 실시하고 그 결과를 정성적으로 분석하였다. 본 연구의 결과, 판의 경계에 대한 고등학생들의 정신모형의 유형은 소박한 모형(naive model), 불안정 모형(unstable model), 인과적 모형(causal model), 개념적 모형(conceptual model)의 4가지로 분류되었다. 이러한 정신모형에 대한 분석 준거는 판과 맨틀을 구분하는지, 판과 하부 맨틀의 이동을 파악하는지, 판의 경계 지형의 특징을 인식하는지, 맨틀의 대류와 지형의 특징을 관련짓고 있는지 등의 요인이다. 판의 경계에 대한 '소박한 모형'과 '불안정 모형'을 지닌 학생들은 맨틀의 대류와 지형의 생성원인을 관련짓지 못한 반면, '인과적 모형'과 개념적 모형'을 지닌 학생들은 판의 경계에서 맨틀 대류와 지형의 생성과의 인과 관계를 인식하고 있었다. 정신모형 유형에 따라 꼭꼭 획득의 방법에 관한 학생들의 믿음을 조사한 결과, 소박한 모형과 불안정 모형을 지닌 학생들은 외부적인 권위에 의존하는 경향을 나타내었다.

• 한국간호교육학회지
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• 제10권1호
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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

• 대한건축학회논문집:구조계
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• 제35권12호
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• pp.181-188
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• 2019

The maintenance of school building is pivotal issue. However, it is difficult to obtain basic analysis data for LCC(Lifecycle Cost) analysis and maintenance planning of school building. Therefore, this study proposed System Dynamics(SD) techniques to make maintenance decisions for school building. The interaction between the major parameters related to the aging of a building, maintenance activities, and cost were expressed in Causal Loop Diagram. Based on this, the formula for the relationship between causal maps was defined and converted to Stock and Flow Diagram. Through the completed SD model the 50-year plan of 214 educational building were tested by considered in account budget, maintainability, and budget allocation opinions. As a result, the integrated SD model demonstrated that it can support strategic decision making by identifying the status class and LCC behavior of school buildings by scenario. According to the scenario analysis, the rehabilitation action of preventive maintenance that primarily repairs the buildings in condition grade C showed the best performance improvement effect relative to the cost. Therefore, if the proposed SD model is expanded to consider the effects of other educational policies, the crucial performance improvement budget can be estimated in the long-term perspective.

• 한국산업정보학회논문지
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• 제22권6호
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• pp.71-84
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• 2017

Over the past decade, we have witnessed Serious Debates in MISQ and Other Journals Between Two Camps that have Differing Views on the use of Causal Indicators to Measure Constructs. There is the Camp that advocates Causal Indicators (ADVOCATE) and the Camp that opposes Their Usage (OPPONENT). The Debates have been primarily centered on the OPPONENT's Argument that the Meaning of a Latent Variable is determined by its Outcome Variables. However, Little Effort has been made to Validate the ADVOCATE's Dispute (Against the OPPONENT's Arguments) that the Meaning of a Latent Variable is decided by its Causal Indicators if there is no Misspecification. Our Study precisely examines the Integrity of the Argument. For this, we empirically examine how the two Primary Psychometric Properties-Comprehensiveness and Interrelationship-of Causal Indicators Influence Theory Testing between Latent Variables through Three Different Tests (i.e., Comprehensive Test, Interrelationship Test, and Mixed Test). Conducted on Two Different Datasets, Our Analysis Consistently Reveals that Structural Path Coefficients are Hardly Sensitive to the Changes (i.e., Misspecification) in the Properties of Causal Indicators. The Discovery offers Important Evidence that the Sound Theoretical Logic of a Causal Model is not in Sync with the Empirical Mechanism of Parameter Estimation. This Underscores that a Latent Variable Formed by Causal Indicators is empirically an elusive notion that is Difficult to Operationalize. As Our Results have Significant Implications on the Integrity of Numerous IS studies which have conducted Theory or Hypothesis Testing Using Causal Indicators, we strongly advocate Open Discussions among Methodologists regarding Our Findings and Their Implications for Both Published IS Research and Future Practices.

• 한국IT서비스학회지
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• 제6권1호
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• pp.47-63
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• 2007

A lot of researchers have been interested in the factors influencing the use of mobile phone services. Most of the previous studies, however, verified only the research models developed by the authors. They did not consider which model agrees better with the real situation. This study presents six alternative models based on various previous studies, and compares the data fitness of the models. A Web survey of mobile phone users collected 2,217 cases. Statistical analyses, using SEM (Structural Equation Modeling), show that the fitness of the simplest alternative model is better than that of any other model. The simplest model has no causal relationship among exogenous factors, and proposes that all of exogenous factors have direct impacts on the customer satisfaction. In addition, the analyses say that corporate and brand image and additional service are more important than the other exogenous factors such as communication quality.