• 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.

• 응용통계연구
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• 제33권4호
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• pp.365-377
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• 2020

선형모형에서 두개 이상의 설명변수들 사이에 존재하는 다중공선성 문제를 변수들 간에 내재되어 있는 공통의 구조인 인자를 구성하고, 인자들을 회귀변수로 사용하여 해결하는 인자회귀모형에 대하여 논의한다. 무한개로 가정 가능한 내재된 인자 중 유의미한 인자적재행렬을 구성하기 위하여 벌점모수의 값이 큰 LASSO 사전분포를 적용하는 베이지안 추정법을 사용한다. 결정된 인자적재행렬과 다른 모수들의 추정값을 각 설명변수의 선형모수로 역변환 하여, 새로운 관측값에 대한 예측 모형으로도 사용한다. 제안한 방법을 제품 서비스 관리 자료에 적용하여 정해진 인자의 개수에 대한 인자가 일반적인 공통인자회귀모형과 동일한 결과를 나타냄을 확인하였고, 일반적인 공통인자회귀모형과 비교를 위해 계산한 평균 제곱 오차값이 더 작다는 것을 알 수 있었다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.633-636
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• 2006

In order to determine new settings of key process variables optimally, a new rule induction method through a historical data is proposed without using an explicit functional model between process and quality variables. First, a partial least square is used to reduce the dimensionality of the process variables. Then new process settings that yield the best quality variable are identified by sequentially partitioning the reduced latent variable space using a patient rule induction method. The proposed method is illustrated with a case study obtained from steel-making processes. We also show, through simulation, that the proposed method gives more stable results than estimating an explicit function even when the form of the function is known in advance.

• 설비공학논문집
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• 제15권2호
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• pp.137-143
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• 2003

In the forming of an integrated system of radiant floor cooling and dehumidifying, chilled coil can be used for cooling and dehumidification. Therefore, it is necessary to find the efficient control method which can eliminates latent load efficiently. This study has been conducted to find this method by dividing the dehumidification system into 3 types according to the control variables and analyzing characteristics of each system. To prevent the floor surface condensation, the amount of condensation can be manipulated by water temperatures, water flow rates in chilled coil, and air flow rates passing by it. So dehumidification system control can be divided into constant air flow control and variable air flow control. Regarding dehumidification control, variable air flow control, which eliminates latent load rather than sensible load, is preferable to constant flow control.

• International Journal of Human Ecology
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• 제8권2호
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• pp.75-83
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• 2007

Korean secondary school students (n=263) responded to surveys measuring their family contexts and school adjustment during the time period August-September 2004. Structure Equation Modeling tests were conducted to identify the nested model on school adjustment, a latent variable constructed with peer relations, teacher-adolescent relations, and academic attitude. In the nested model, parental involvement was a powerful predictor for school adjustment. Family conflict had a negative impact on school adjustment and was statistically significantly when correlated with the other predictors in the model. These finding suggested that family contexts play an important role in Korean adolescents' school adjustment. Hence, adolescents' perceived GPA level and satisfaction for school were important predictors for school adjustment.

• 응용통계연구
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• 제24권4호
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• pp.609-622
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• 2011

The pattern of methylation draws significant attention from cancer researchers because it is believed that DNA methylation and gene expression have a causal relationship. As the interest in the role of methylation patterns in cancer studies (especially drug resistant cancers) increases, many studies have been done investigating the association between gene expression and methylation. However, a model-based approach is still in urgent need. We developed a finite mixture model in the Bayesian framework to find a possible relationship between gene expression and methylation. For inference, we employ Expectation-Maximization(EM) algorithm to deal with latent (unobserved) variable, producing estimates of parameters in the model. Then we validated our model through simulation study and then applied the method to real data: wild type and hydroxytamoxifen(OHT) resistant MCF7 breast cancer cell lines.

• 음성과학
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• 제11권4호
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• pp.75-88
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• 2004

In this paper, we propose a new approach to sequential linear regression adaptation of continuous density hidden Markov models (CDHMMs) based on transformation space model (TSM). The proposed TSM which characterizes the a priori knowledge of the training speakers associated with maximum likelihood linear regression (MLLR) matrix parameters is effectively described in terms of the latent variable models. The TSM provides various sources of information such as the correlation information, the prior distribution, and the prior knowledge of the regression parameters that are very useful for rapid adaptation. The quasi-Bayes (QB) estimation algorithm is formulated to incrementally update the hyperparameters of the TSM and regression matrices simultaneously. Experimental results showed that the proposed TSM approach is better than that of the conventional quasi-Bayes linear regression (QBLR) algorithm for a small amount of adaptation data.

• 한국음향학회지
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• 제41권6호
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• pp.662-667
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• 2022

음악 유사도 계산은 음악 검색 서비스 구현에서 가장 중요한 요소 중 하나이다. 본 논문은 커버곡 검색의 성능을 제고하기 위한 음악 유사도 학습에 대해서 다룬다. 음악 유사도 함수를 유도하는 데 확률적 선형 판별 분석을 이용하여 잠재 음악 공간을 구한다. 잠재 음악 공간은 같은 커버곡 간의 거리는 줄이고 다른 곡 간의 거리는 크게 되도록 학습한다. 추출된 음악 특징이 잠재 음악 변수에서 생성되었다는 가정 하에 확률 모델을 구하고, 음악의 동질성 여부를 가설검증하여 음악 유사도 함수를 유도한다. 두 가지 커버곡 실험 데이터셋에서 성능 비교를 수행하여 제안한 음악 유사도 함수가 커버곡 검색 성능을 개선시킬 수 있음을 보였다.

• 한국심리학회지 : 문화 및 사회문제
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• 제28권4호
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• pp.577-595
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• 2022

본 연구는 잠재프로파일 분석을 활용하여 성인 도박자의 심리적 특성을 분류하고, 잠재프로파일에 따른 결과를 확인하고자 하였다. 이를 위해 본 연구는 도박행동 패턴, 기본심리욕구, 및 스트레스, 우울, 불안과 같은 정신건강 수준에 대해 온라인 설문에 참여한 도박자 473명을 대상으로 하였다. 잠재프로파일 분석을 한 결과 성인 도박자의 심리적 특성은 크게 3가지 유형으로 나타났으며, '정신건강-심리욕구 저 집단', '정신건강-심리욕구 중 집단', '정신건강-심리욕구 고 집단'으로 나타났다. 또한, 결과변수인 문제도박 수준은 각 잠재프로파일에 따라 유의하게 다른 차이를 보였으며, 정신건강-심리욕구 저 집단은 문제성 도박, 정신건강-심리욕구 중 집단은 중위험 도박, 정신건강-심리욕구 고 집단은 저위험 도박 수준으로 나타났다. 본 연구는 기존의 도박 문제에 대한 변인 중심의 연구의 한계를 극복하고, 도박자들의 심리적 특성들과 그들의 다른 잠재프로파일에 따른 문제도박 수준의 차이에 대한 새로운 통찰을 제공하였다는 점에서 의의가 있다. 끝으로 본 연구의 한계와 향후 도박문제에 대한 연구방향에 대해서 제언하였다.

• 한국수학교육학회지시리즈A:수학교육
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• 제50권1호
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• pp.103-118
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• 2011

The study examined whether the relation between mathematics self-efficacy and mathematics achievement was partially mediated by the learning strategies, using latent growth model analyses. It was also examined the auto-regressive, cross-lagged (ARCL) panel model for testing the stability and change in the relation of mathematics self-efficacy and learning strategy over time. The study analyzed the first-year to the third-year data of the Korean Educational Longitudinal Survey (KELS). The result of ARCL panel model analysis showed that earlier mathematics self-efficacy could predict later learning strategy use. There were linear trends in mathematics self-efficacy, learning strategy, and mathematics achievement. Specifically, mathematics achievement was increased over the three time points, whereas mathematics self-efficacy and learning strategies were significantly decreased. In the analyses of latent growth models, the mediating effects of learning strategies were overall supported. That is, both of initial status and change rate of rehearsal strategy partially mediated the relation of mathematics self-efficacy and mathematics achievement. However, in elaboration and meta-cognitive strategies, only the initial status of each variable showed the indirect relationship.