• 제목/요약/키워드: Ordinal Data

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Visualizations for Matched Pairs Models Using Modified Correspondence Analysis

  • Lee, Chanyoon;Choi, Yong-Seok
    • Communications for Statistical Applications and Methods
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    • 제21권4호
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    • pp.275-284
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    • 2014
  • Matched pairs are twice continuously measured data with the same categories. They can be represented as the square contingency tables. We can also consider symmetry and marginal homogeneity. Moreover, we can infer the matched pairs models; the symmetry model, the quasi-symmetry model, and the ordinal quasi-symmetry model. These inferences are involved in assumptions for special distributions. In this study, we visualize matched pairs models using modified correspondence analysis. Modified correspondence analysis can be used when square contingency tables are given; consequently, it is involved in the square and asymmetric correspondence matrix. This technique does not need assumptions for special distributions and is more helpful than the correspondence analysis to visualize matched pairs models.

Active training machine with muscle activity sensor for elderly people

  • Matsuda, Goichi;Tanaka, Motohiro;Yoon, Sung-Jae;Ishimatsu, Takakazu;Kim, Seok-Hwan;Moromugi, Shunji
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1169-1172
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    • 2005
  • For elderly people, an advanced training machine that uses actuator and can adjust load according to muscle activity is proposed. The proposed machine allows users to have a safe and effective training through exercise close to ordinal motion appears in daily life such as stretching or stooping motion. A muscle activity sensor real-timely monitors the activation level of user's muscle during the exercise and the training load is adjusted based on the measured data. The training load is exerted and continuously controlled by electric/pneumatic actuator.

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범주형 자료 분석을 위한 LAD 추정량 (LAD Estimators for Categorical Data Analysis)

  • 최현집
    • 응용통계연구
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    • 제16권1호
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    • pp.55-69
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    • 2003
  • 일반적인 다차원 분할표 분석을 위해 고려 할 수 있는 로그 선형 모형 (log-linear model)과 순위 변수(ordered variables)가 고려된 여러 연관성 모형(association models)을 위한 가중값이 부여된 LAD(least absolute deviations) 추정량을 제안하고 추정을 위한 반복 추정법을 제안하였다. 모의실험을 통하여 제안된 LAD추정량이 최우추정량에 비해 로버스트한 성질을 갖는 다는 것을 밝히고, 이상칸 식별을 위해 많은 선행 연구들에서 인용된 자료들의 경험적 분석을 통해 제안된 추정량과 추정방법이 가질 수 있는 문제점과 특징에 관하여 토론하였다

신경망 분리모형과 사례기반추론을 이용한 기업 신용 평가 (Corporate Credit Rating using Partitioned Neural Network and Case- Based Reasoning)

  • 김다윗;한인구;민성환
    • Journal of Information Technology Applications and Management
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    • 제14권2호
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    • pp.151-168
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    • 2007
  • The corporate credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this study, the corporate credit rating model employs artificial intelligence methods including Neural Network (NN) and Case-Based Reasoning (CBR). At first we suggest three classification models, as partitioned neural networks, all of which convert multi-group classification problems into two group classification ones: Ordinal Pairwise Partitioning (OPP) model, binary classification model and simple classification model. The experimental results show that the partitioned NN outperformed the conventional NN. In addition, we put to use CBR that is widely used recently as a problem-solving and learning tool both in academic and business areas. With an advantage of the easiness in model design compared to a NN model, the CBR model proves itself to have good classification capability through the highest hit ratio in the corporate credit rating.

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A New Constrained Parameter Estimation Approach in Preference Decomposition

  • Kim, Fung-Lam;Moy, Jane W.
    • Industrial Engineering and Management Systems
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    • 제1권1호
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    • pp.73-78
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    • 2002
  • In this paper, we propose a constrained optimization model for conjoint analysis (a preference decomposition technique) to improve parameter estimation by restricting the relative importance of the attributes to an extent as decided by the respondents. Quite simply, respondents are asked to provide some pairwise attribute comparisons that are then incorporated as additional constraints in a linear programming model that estimates the partial preference values. This data collection method is typical in the analytic hierarchy process. Results of a simulation study show the new model can improve the predictive accuracy in partial value estimation by ordinal east squares (OLS) regression.

Depressive Symptoms and Menstrual Cycle Irregularity among Community Women of Childbearing Age

  • Heeja Jung;Yanghee Pang
    • International Journal of Advanced Culture Technology
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    • 제11권2호
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    • pp.109-117
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    • 2023
  • Menstrual cycle irregularity reflects the reproductive health of women of childbearing age, but studies are scant on women in communities. In this study, we identified factors associated with menstrual cycle irregularity among 884 community women of childbearing age (19-40 years) and confirmed the relationship between menstrual cycle irregularity and depressive symptoms. Data were collected through online or mobile platforms. We noted that 25% of participants had menstrual cycle irregularity. Multivariable ordinal logistic regression analysis revealed that age, irregular eating, and depressive symptoms were associated with menstrual cycle irregularity. After adjusting for confounding variables, participants with depressive symptoms were at a slightly higher risk of menstrual cycle irregularity (odds ratio = 1.078, confidence interval = 1.021-1.139). Additional support be provided for community-living women of childbearing age with depressive symptoms, to improve their reproductive health

산모의 생활스트레스, 사회적 지지 및 우울의 관계 (The Relationship Among the Degrees of Life Stress, Social Support and Depression in Postpartal Women)

  • 최순희
    • 기본간호학회지
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    • 제8권2호
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    • pp.199-209
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    • 2001
  • The purpose of this study was to examine the relationship between life stress and depression, and the effect of social support in postpartal $4{\sim}6$ week women. Theoretically social support is thought to mediate the relationship between life stress and depression. Data were collected from June 1 to July 30, 1999. The data were analysed by use of SPSS. Two hypotheses were tested using Gamma, a measure of association for ordinal variables. Partial gamma was used to test the third hypothesis. Patterns of elaboration described by Babbie(1986) were selected to interpret the relationship of the three variables in the analyses. The results of this study are summarized as follows ; There was a positive relationship between life stress and depression (Gamma=.45, P=.017), and an inverse relationship between social support and depression (Gamma=-.49, P=.009). Thus the first, two hypotheses were supported. 2. When social support was controlled, the relationship between life stress and depression increased under the condition of low social support, but with high social support, the relationship decreased. It can be interpreted that life stresses are positively related to depression under the condition of low social support, however this relationship cannot be expected with high social support.

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삼각퍼지수를 이용한 시계열모형 (Time Series Using Fuzzy Logic)

  • 정혜영;최승회
    • Communications for Statistical Applications and Methods
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    • 제15권4호
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    • pp.517-530
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    • 2008
  • 본 논문은 시간의 흐름에 따라 일정한 간격으로 관측된 시계열자료에 대한 통계적인 관계를 추정하기 위하여 삼각퍼지수를 이용한 퍼지시계열모형을 소개한다. 모든 관측치를 포함하는 전체집합을 분할하는 구간을 자료의 빈도수에 따라 결정하고 연속되는 두 시점에서 퍼지수가 일치하는 경우에는 관측된 자료의 차에 대한 정보를 이용하여 제안된 퍼지시계열모형을 추정한다. 예제를 이용하여 제안된 퍼지시계열모형의 정확성을 일반적인 시계열모형과 여러 가지 방법으로 추정된 퍼지시계열모형과 비교한다.

모의 실험을 이용한 여러 합치도들의 비교 (A simulation study of rater agreement measures)

  • 한경도;박용규
    • Journal of the Korean Data and Information Science Society
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    • 제23권1호
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    • pp.25-37
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    • 2012
  • 두 평정자간 평가의 일치정도를 나타내는 합치도로 Cohen (1960)의 ${\pi}$, Scott (1955)의 H, 박미희와 박용규 (2007)의 등 많은 통계량이 제안되어왔다. 모의실험을 통하여 균형적 주변분포에서의 명목형과 순서형 합치도, 두 가지 역설이 발생하는 불균형 주변분포에서의 명목형 합치도들의 편의, 표준오차, 평균오차제곱 분산, 변이계수를 비교한 결과, 모든 경우에서 AC1과 H의 표준오차와 변이계수가 가장 작게 나타났다.

Public Reporting on the Quality Ratings of Nursing Homes in the Republic of Korea

  • Lee, Hyang Yuol;Shin, Juh Hyun
    • 대한간호학회지
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    • 제49권2호
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    • pp.161-170
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    • 2019
  • Background: Quality ratings could provide vital information to help people in choosing a nursing home. Purpose: This study investigated factors aligned with quality ratings of nursing homes. Methods: We employed a cross-sectional descriptive design to assess publicly available data on 1,354 nursing homes with 30 or more beds in the Republic of Korea. After excluding 289 nursing homes with no reported quality-evaluation ratings, we analyzed the 2015 data of 1,065 nursing homes. To prevent multicollinearity among independent variables, we carefully selected the final set of variables based on clinical and theoretical meaningfulness to direct nursing care. Quality, the ordinal outcome, was scored from 1 to 5 with a higher score indicating higher quality of the organization. We constructed a multivariate ordered logistic regression model. Results: Higher quality ratings of nursing homes was significantly related to the number of unoccupied beds (OR=0.99, p=.024), registered nurses (RNs) (OR=1.30, p=.003), qualified care workers (OR=1.03, p=.011), cognitive-improvement programs (OR=1.05, p=.024), and other programs for residents' activities (OR=1.09, p<.001). Conclusion: The number of RNs had the strongest influence on the publicly reported quality rating, while the rating of qualified care workers demonstrated little effect and that of nursing assistants had no effect. The number of RNs could be used as a crucial indicator for high-quality homes; more resident-engaging programs also demonstrated better quality of nursing home care.