• Title/Summary/Keyword: statistical correlation

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P-value calculation methods for semi-partial correlation coefficients

  • Kim, Seongho
    • Communications for Statistical Applications and Methods
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    • v.29 no.3
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    • pp.397-402
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    • 2022
  • The mathematical expression of the p-value calculation for the semi-partial correlation coefficient differs between Kim (2015) and Cohen et al. (2003). These two expressions were compared and the advantages of Kim (2015)'s approach over Cohen et al. (2003) were discussed.

ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients

  • Kim, Seongho
    • Communications for Statistical Applications and Methods
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    • v.22 no.6
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    • pp.665-674
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    • 2015
  • Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

Canonical Correlation Biplot

  • Park, Mi-Ra;Huh, Myung-Hoe
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.11-19
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    • 1996
  • Canonical correlation analysis is a multivariate technique for identifying and quantifying the statistical relationship between two sets of variables. Like most multivariate techniques, the main objective of canonical correlation analysis is to reduce the dimensionality of the dataset. It would be particularly useful if high dimensional data can be represented in a low dimensional space. In this study, we will construct statistical graphs for paired sets of multivariate data. Specifically, plots of the observations as well as the variables are proposed. We discuss the geometric interpretation and goodness-of-fit of the proposed plots. We also provide a numerical example.

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A Comment for Teaching Correlation Coefficient in Elementary Statistics Course

  • Oh, Myong-Sik
    • Communications for Statistical Applications and Methods
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    • v.14 no.2
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    • pp.301-307
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    • 2007
  • A effective teaching method on correlation coefficient for elementary level statistics course is discussed in this article. The well known inequalities, such as Theorem 368 of Hardy et al. (1952), are used for the interpretation of concept of covariance. An Excel example is provided for the illustration of concept of correlation coefficient.

A dynamic Bayesian approach for probability of default and stress test

  • Kim, Taeyoung;Park, Yousung
    • Communications for Statistical Applications and Methods
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    • v.27 no.5
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    • pp.579-588
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    • 2020
  • Obligor defaults are cross-sectionally correlated as obligors share common economic conditions; in addition obligors are longitudinally correlated so that an economic shock like the IMF crisis in 1998 lasts for a period of time. A longitudinal correlation should be used to construct statistical scenarios of stress test with which we replace a type of artificial scenario that the banks have used. We propose a Bayesian model to accommodate such correlation structures. Using 402 obligors to a domestic bank in Korea, our model with a dynamic correlation is compared to a Bayesian model with a stationary longitudinal correlation and the classical logistic regression model. Our model generates statistical financial statement under a stress situation on individual obligor basis so that the genearted financial statement produces a similar distribution of credit grades to when the IMF crisis occurred and complies with Basel IV (Basel Committee on Banking Supervision, 2017) requirement that the credit grades under a stress situation are not sensitive to the business cycle.

A GENERALIZATION OF THE INTRACLASS CORRELATION IN CLUSTER SAMPLING

  • KIM KYU-SEONG
    • Journal of the Korean Statistical Society
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    • v.34 no.3
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    • pp.185-195
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    • 2005
  • This article is concerned with the intraclass correlation in survey sampling. From a design-based viewpoint the intraclass correlation is generalized to a finite population with unequal sized clusters. Under simple random cluster sampling the intraclass correlation is given in an explicit form, which is a generalization of the usual one. The range of it is found and the design effect is expressed by means of it. An example is given to compare the intraclass correlation with the homogeneity measure numerically, which shows that two measures are not the same except some limited cases.

An Agglomerative Hierarchical Variable-Clustering Method Based on a Correlation Matrix

  • Lee, Kwangjin
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.387-397
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    • 2003
  • Generally, most of researches that need a variable-clustering process use an exploratory factor analysis technique or a divisive hierarchical variable-clustering method based on a correlation matrix. And some researchers apply a object-clustering method to a distance matrix transformed from a correlation matrix, though this approach is known to be improper. On this paper an agglomerative hierarchical variable-clustering method based on a correlation matrix itself is suggested. It is derived from a geometric concept by using variate-spaces and a characterizing variate.

Graphical Methods for Correlation and Independence

  • Hong, Chong-Sun;Yoon, Jang-Sub
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.219-231
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    • 2006
  • When the correlation of two random variables is weak, the value of one variable can not be used effectively to predict the other. Even when most of the values are overlapped, it is difficult to find a linear relationship. In this paper, we propose two graphical methods of representing the measures of correlation and independence between two random variables. The first method is used to represent their degree of correlation, and the other is used to represent their independence. Both of these methods are based on the cumulative distribution functions defined in this work.

A Comparative Study on the Knowledge, Attitude and Behavior of Community regarding Irradiated Foods in Incheon Area (방사선조사식품의 지식, 태도, 행위에 관한 비교 연구)

  • Hwang, Seong-Hee;Jang, Jae Seon
    • The Korean Journal of Food And Nutrition
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    • v.29 no.2
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    • pp.246-252
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    • 2016
  • This paper presents basic supporting data necessary for planning an educational intervention strategy as part of a communication strategy that would form an extensive national consensus on and enhance national understanding of irradiated foods. A survey was conducted to collect data on the knowledge, attitude, and behavior with regard to irradiated foods among community. It appeared 133 male (36.5%) and 231 women persons (63.5%). After irradiated food were analyzed, whole knowledge, attitude, and behavior standard to the irradiated food is 2.32, 11.90, and 12.92 scores respectively. The knowledge, attitude, behavior of irradiated foods according to person characteristics were analyzed. The knowledge on irradiated food was statistical difference by gender, age, education standard and occupation (p<0.05), whereas no statistical difference marriage (p>0.05). The attitude on irradiated food was statistical difference by age, education standard and occupation (p<0.05), whereas no statistical difference gender (p>0.05). The behavior on irradiated food was statistical difference by age, education standard and occupation (p<0.05), whereas no statistical difference gender and marriage (p>0.05). The coefficient of correlation of knowledge and attitude in irradiated food showed positive correlation of r=0.324 (p<0.01). The coefficient of correlation of knowledge and behavior in irradiated food showed negative correlation of r=-0.118 (p<0.05). The coefficient of correlation of attitude and behavior in irradiated food showed negative correlation of r=-0.316 (p<0.01).

Correlation plot for a contingency table

  • Hong, Chong Sun;Oh, Tae Gyu
    • Communications for Statistical Applications and Methods
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    • v.28 no.3
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    • pp.295-305
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    • 2021
  • Most graphical representation methods for two-dimensional contingency tables are based on the frequencies, probabilities, association measures, and goodness-of-fit statistics. In this work, a method is proposed to represent the correlation coefficients for each of the two selected levels of the row and column variables. Using the correlation coefficients, one can obtain the vector-matrix that represents the angle corresponding to each cell. Thus, these vectors are represented as a unit circle with angles. This is called a CC plot, which is a correlation plot for a contingency table. When the CC plot is used with other graphical methods as well as statistical models, more advanced analyses including the relationship among the cells of the row or column variables could be derived.