• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.575-587
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• 2015

The development in data collection techniques results in high dimensional data sets, where discrimination is an important and commonly encountered problem that are crucial to resolve when high dimensional data is heterogeneous (non-common variance covariance structure for classes). An example of this is to classify microbial habitat preferences based on codon/bi-codon usage. Habitat preference is important to study for evolutionary genetic relationships and may help industry produce specific enzymes. Most classification procedures assume homogeneity (common variance covariance structure for all classes), which is not guaranteed in most high dimensional data sets. We have introduced regularized elimination in partial least square coupled with QDA (rePLS-QDA) for the parsimonious variable selection and classification of high dimensional heterogeneous data sets based on recently introduced regularized elimination for variable selection in partial least square (rePLS) and heterogeneous classification procedure quadratic discriminant analysis (QDA). A comparison of proposed and existing methods is conducted over the simulated data set; in addition, the proposed procedure is implemented to classify microbial habitat preferences by their codon/bi-codon usage. Five bacterial habitats (Aquatic, Host Associated, Multiple, Specialized and Terrestrial) are modeled. The classification accuracy of each habitat is satisfactory and ranges from 89.1% to 100% on test data. Interesting codon/bi-codons usage, their mutual interactions influential for respective habitat preference are identified. The proposed method also produced results that concurred with known biological characteristics that will help researchers better understand divergence of species.

• 한국조사연구학회:학술대회논문집
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• 한국조사연구학회 2001년도 춘계학술대회
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• pp.109.2-130
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• 2001

이 논문의 목적은 상관분석에서 집단차 변수를 무시하였을 때 자료에 대한 잘못된 해석을 유도할 수 있음을 보여주고, 집단차를 고려한 분석의 중요성과 그 방법을 제시하는 것이었다. 연구 1은 시뮬레이션 연구로 상관구조에 대한 분석인 요인분석에서 집단차를 무시하면 자료가 지니고 있던 요인구조를 파악하지 못함을 보여주었다. 이에 대한 대비책으로 표준점수에 의한 자료의 변환 방법과 공분산 구조모형의 집단분석을 이용하는 방법등이 제시되었다. 연구 2는 사례연구로 실제 자료에서 집단의 평균차에 의한 효과가 발생하는지를 지능검사 자료를 이용하여 예증하고 이러한 문제점을 해결할 수 있는지를 보여주었다.

• 한국조사연구학회지:조사연구
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• 제2권2호
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• pp.109-130
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• 2001

이 논문의 목적은 상관분석에서 집단차 변수를 무시하였을 때 자료에 대한 잘못된 해석을 유도 할 수 있음을 보여주고, 집단차를 고려한 분석의 중요성과 그 방법을 제시하는 것이었다. 연구 1은 시뮬레이션 연구로 상관구조에 대한 분석인 요인분석에서 집단차를 무시하면 자료가 지니고 있던 요인구조를 파악하지 못함을 보여주었다. 이에 대한 대비책으로 표준점수에 의한 자료의 변환방법과 공분산 구조모형의 집단분석을 이용하는 방법 등이 제시되었다. 연구 2는 사례연구로 실제 자료에서 집단의 평균차에 의한 효과가 발생하는지를 지능검사 자료를 이용하여 예증하고 이러한 문제점을 해결할 수 있는지를 보여주었다.

• 한국산학기술학회논문지
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• 제17권7호
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• pp.629-640
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• 2016

본 연구는 치과위생사들의 직무스트레스, 피로증상 및 직무만족도가 이직의도에 미치는 영향을 규명할 목적으로 사도하였다. 연구대상은 치과 병 의원에 근무하고 있는 치과위생사 516명을 대상으로 2015년 4월 1일부터 6월 30일까지의 기간 동안에 자기기입식 설문지를 이용한 설문조사를 실시하였다. 자료의 분석은 각 독립변수에 대한 이직의도의 평균점수를 비교하였으며 t-test 및 ANOVA로 검정하였다. 또한 직무스트레스, 피로증상, 직무만족도 및 이직의도 간의 Pearson상관분석에 의한 상관계수를 구하였으며, 공분산구조분석을 사용하여 이직의도와 직무스트레스, 피로증상 및 직무만족도와의 관련성을 평가하였다. 연구결과, 조사대상자의 이직의도는 직무스트레스가 높은 군일수록, 피로증상이 높은 군일수록, 직무만족도가 낮은 군일수록 유의하게 높았다. 조사대상자의 이직의도는 직무스트레스 및 피로증상과는 유의한 양의 상관관계를 보인 반면, 직무만족도와는 유의한 음의 상관관계를 보였다. 공분산 구조분석 결과, 직무스트레스는 피로증상이나 직무만족도보다 이직의도에 더 큰 영향을 미쳤으며, 직무스트레스와 피로증상이 높고, 직무만족도가 낮을수록 이직의도를 높이는 효과가 있는 것으로 나타났다. 위와 같은 결과는 치과위생사들의 이직의도는 피로증상이나 직무만족도보다 직무스트레스에 의해 더 큰 영향을 받고 있음을 알 수 있다. 따라서 치과위생사들의 이직의도를 낮추기 위해서는 직무스트레스 및 피로를 감소시키고, 직무만족도를 향상시키기 위한 노력이 필요할 것으로 생각된다.

• Communications for Statistical Applications and Methods
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• 제30권4호
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• pp.389-402
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• 2023

Multivariate or clustered failure time data often occur in many medical, epidemiological, and socio-economic studies when survival data are collected from several research centers. If the data are periodically observed as in a longitudinal study, survival times are often subject to various types of interval-censoring, creating multivariate interval-censored data. Then, the event times of interest may be correlated among individuals who come from the same cluster. In this article, we propose a unified linear regression method for analyzing multivariate interval-censored data. We consider a semiparametric multivariate accelerated failure time model as a statistical analysis tool and develop a generalized Buckley-James method to make inferences by imputing interval-censored observations with their conditional mean values. Since the study population consists of several heterogeneous clusters, where the subjects in the same cluster may be related, we propose a generalized estimating equations approach to accommodate potential dependence in clusters. Our simulation results confirm that the proposed estimator is robust to misspecification of working covariance matrix and statistical efficiency can increase when the working covariance structure is close to the truth. The proposed method is applied to the dataset from a diabetic retinopathy study.

• 한국과학교육학회지
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• 제17권1호
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• pp.1-10
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• 1997

The purpose of this study was to analyze the structural model of causal effects of students' variables on science process skills. Student characteristics investigated in the study included attitude related to the science, logical thinking ability, scientific experiences, cognitive style. Covariance structural modeling procedures were used to test causal inferences about hypothesized relationships. The sample consisted of 319 6th grade students and 321 8th grade students in Seoul City, Korea. Five instruments were used in the study, TSPS(test of science process skills), GALT(group assessment of logical thinking), CEFT(children embedded figures test), questionnaire of attitude related to the science, questionnaire of scientific experience. For statistical analysis, the study adopted the structural equation modeling with LlSREL, a computer statistical program developed by J reskog and S rbom. Major findings of the study are as follows:1) Logical thinking ability has a most strong direct effect on science process skills. 2) The structural coefficient of scientific experience influence on attitude related to the science has the greatest direct one than the others in the covariance structural model. According to the results of this study, it is very importance that various scientific experiences, particularly hands-on activity, should be offer to students to improve science process skills. Also, understanding the relationships of student variable to science process skills will be helpful to decision making on the part of curriculum developers, science teachers and researchers.

• 근관절건강학회지
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• 제5권1호
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• pp.7-25
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• 1998

Rheumatoid arthritis, unlike other chronic diseases, causes the patients to experience uncertainty in their daily lives and thus to feel threat on their emotional comfort because of inconsistent and unpredictable symptoms such as pain. Therefore, a theoretical framework is needed for explanation of uncertainty in patients having rheumatoid arthritis. A hypothetical model was constructed on the basis of Mishel's Uncertainty Theory and other literature review. The model included 9 theoretical concepts and 19 paths. Subjects of the study constituted 330 partients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. Self report questionnaires were used to measure the variables affecting uncertainty. Reliability coefficients of these instruments were found Cronbach's Alpha=$.70{\sim}.94$. In data analysis, SAS program and PC-LISREL 8.03 computer program were utilized for descriptive statistics and covariance structure analysis. The results of covariance structure analysis for model fitness were as follows : 1) Hypothetical model showed a good fit to the empirical data : Chi-square($X^2$)=41.81 (df=11, P=.000), Goodness of Fit Index=.974, Root Mean Square Residual=.049, Normed Fit Index=.928, Non Normed Fit Index=.814. 2) For the validity and the parcimony of model, a modified model was constructed by appending 2 paths and deleting 5 paths according to the criteria of statistical significance and meaningfulness. 3) The results of hypothesis testing were as follows : (1) Educational level, event familiarity and severity of illness had a direct effect on uncertainty : Event congruency had both direct and indirect effect on uncertainty : Credible authority and symptom consistency had a nonsignificant direct effect on uncertainty, (2) Illness duration, symptom consistency, and event congruency had a direct effect on severity of illness ; Credible authority had a both direct and indirect effect on severity of illness ; Event congruency had the greatest effect on severity of illness, and event familiarity had a nonsignificant direct effect on severity of illness.

• Journal of Preventive Medicine and Public Health
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• 제40권5호
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• pp.351-362
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• 2007

Objectives: The present study was intended to assess the mental health of nurses working for university hospitals and to establish which factors determine their mental health. Methods: Self-administered questionnaires were given to 1,486 nurses employed in six participating hospitals located in Daejeon City and Chungnam Province between July 1 st and August 31st, 2006. The questionnaire items included sociodemographic, job-related, and psychosocial factors, with job stress factors (JCQ) as independent variables and indices of mental health status (PWI, SDS and MFS) as dependent variables. For statistical analysis, the Chi-square test was used for categorical variables, with hierarchical multiple regression used for determining the factors effecting mental health. The influence of psychosocial and job-related factors on mental health status was assessed by covariance structure analysis. The statistical significance was set at p<0.05. Results: The factors influencing mental health status among subject nurses included sociodemographic characteristics such as age, number of hours of sleep, number of hours of leisure, and subjective health status; job-related characteristics such as status, job satisfaction, job suitability, stresses such as demands of the job, autonomy, and coworker support; and psychosocial factors such as self-esteem, locus of control and type A behavior patterns. Psychosocial factors had the greatest impact on mental health. Covariance structure analysis determined that psychosocial factors affected job stress levels and mental health status, and that the lower job stress levels were associated with better mental health. Conclusions: Based on the study results, improvement of mental health status among nurses requires the development and application of programs to manage job stress factors and/or psychosocial factors as well as sociodemographic and job-related characteristics.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.751-760
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• 2017

In recent years, multifractal-based analysis methods have been widely applied in engineering. Among these methods, multifractal detrended cross-correlation analysis (MFDXA), a branch of fractal analysis, has been successfully applied in the fields of finance and biomedicine. For its great potential in reflecting the subtle characteristic among signals, a structural health monitoring (SHM) system based on MFDXA is proposed. In this system, damage assessment is conducted by exploiting the concept of multifractal theory to quantify the complexity of the vibration signal measured from a structure. According to the proposed algorithm, the damage condition is first distinguished by multifractal detrended fluctuation analysis. Subsequently, the relationship between the q-order, q-order detrended covariance, and length of segment is further explored. The dissimilarity between damaged and undamaged cases is visualized on contour diagrams, and the damage location can thus be detected using signals measured from different floors. Moreover, a damage index is proposed to efficiently enhance the SHM process. A seven-story benchmark structure, located at the National Center for Research on Earthquake Engineering (NCREE), was employed for an experimental verification to demonstrate the performance of the proposed SHM algorithm. According to the results, the damage condition and orientation could be correctly identified using the MFDXA algorithm and the proposed damage index. Since only the ambient vibration signal is required along with a set of initial reference measurements, the proposed SHM system can provide a lower cost, efficient, and reliable monitoring process.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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• pp.352-361
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• 2003

We have evaluated the extent of saltwater intrusion from electrical resistivity distribution in a coastal aquifer system in the southeastern part of Busan, Korea. This aquifer system is divided into four layers according to the hydrogeologic characteristics and the horizontal extent of intruded saltwater is determined at each layer through the geostatistical interpretation of electrical resistivity data. In order to define the statistical structure of electrical resistivity data, variogram analysis is carried out to obtain best generalized covariance models. IRF-k (intrinsic random function of order k) kriging is performed with covariance models to produce the plane of spatial mean resistivities. The kriged estimates are evaluated by cross validation to show a good agreement with the true values and the statistics of cross validation represented low errors for the estimates. In the resistivity contour maps more than 5 m below the surface, we can see a dominant direction of saltwater intrusion beginning from the east side. The area of saltwater intrusion increases with depth. The northeast side has low resistivities less than 5 ohm-m due to the presence of saline water in the depth range of 20 m through 70 m. These results show that the application of geostatistical technique to electrical resistivity data is useful for assessing saltwater intrusion in a coastal aquifer system.