The Experts below are selected from a list of 297 Experts worldwide ranked by ideXlab platform
Katie A Haerling - One of the best experts on this subject based on the ideXlab platform.
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making sense of methods and measurement pearson product moment Correlation Coefficient
Clinical Simulation in Nursing, 2014Co-Authors: Susan Prion, Katie A HaerlingAbstract:• This short column provides an overview of the Pearson product-moment Correlation Coefficient.
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making sense of methods and measurement spearman rho ranked order Correlation Coefficient
Clinical Simulation in Nursing, 2014Co-Authors: Susan Prion, Katie A HaerlingAbstract:This short column provides an overview of the Spearman-rho ranked-order Correlation Coefficient.
Susan Prion - One of the best experts on this subject based on the ideXlab platform.
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making sense of methods and measurement pearson product moment Correlation Coefficient
Clinical Simulation in Nursing, 2014Co-Authors: Susan Prion, Katie A HaerlingAbstract:• This short column provides an overview of the Pearson product-moment Correlation Coefficient.
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making sense of methods and measurement spearman rho ranked order Correlation Coefficient
Clinical Simulation in Nursing, 2014Co-Authors: Susan Prion, Katie A HaerlingAbstract:This short column provides an overview of the Spearman-rho ranked-order Correlation Coefficient.
Junhaeng Heo - One of the best experts on this subject based on the ideXlab platform.
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comparison on probability plot Correlation Coefficient test considering skewness of sample for the gev distribution
Journal of Korea Water Resources Association, 2014Co-Authors: Hongjoo Shi, Sooyoung Kim, Junhaeng HeoAbstract:It is important to estimate an appropriate quantile for design of hydraulic structure. For this purpose, it is necessary to find the appropriate probability distribution which can represent the sample data well. Probability plot Correlation Coefficient test as one of goodness-of-fit test, is recently developed and has been known as a simple and powerful method. In this study, probability plot Correlation Coefficient test statistics using the plotting position considering the Coefficients of skewness for the GEV distribution is derived, and represented by the regression equation. Monte-Carlo method is also performed to compare the rejection power between each method. As the results, the probability plot Correlation Coefficient test which is derived in this study is better than the others. In particular, when sample size is small and distribution has the shape parameter, rejection power of probability plot Correlation Coefficient test considering the Coefficients of skewness is bigger than the others.
Joakim Ekström - One of the best experts on this subject based on the ideXlab platform.
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A generalized definition of the polychoric Correlation Coefficient
2011Co-Authors: Joakim EkströmAbstract:We generalize the polychoric Correlation Coefficient to a large class of parametric families of bivariate distributions. The generalized definition agrees with the conventional definition on the fa ...
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on the relation between the polychoric Correlation Coefficient and spearman s rank Correlation Coefficient
Department of Statistics UCLA, 2011Co-Authors: Joakim EkströmAbstract:Spearman’s rank Correlation Coefficient is shown to be a deterministic transformation of the empirical polychoric Correlation Coefficient. The transformation is a homeomorphism under given marginal probabilities, and has a fixed point at zero. Moreover, the two measures of association for ordinal variables are asymptotically equivalent, in a certain sense. If the ordinal variables arise from discretizations, such as groupings of values into categories, Spearman’s rank Correlation Coefficient has some undesirable properties, and the empirical polychoric Correlation Coefficient is better suited for statistical inference about the association of the underlying, non-discretized variables.
Hongjoo Shi - One of the best experts on this subject based on the ideXlab platform.
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comparison on probability plot Correlation Coefficient test considering skewness of sample for the gev distribution
Journal of Korea Water Resources Association, 2014Co-Authors: Hongjoo Shi, Sooyoung Kim, Junhaeng HeoAbstract:It is important to estimate an appropriate quantile for design of hydraulic structure. For this purpose, it is necessary to find the appropriate probability distribution which can represent the sample data well. Probability plot Correlation Coefficient test as one of goodness-of-fit test, is recently developed and has been known as a simple and powerful method. In this study, probability plot Correlation Coefficient test statistics using the plotting position considering the Coefficients of skewness for the GEV distribution is derived, and represented by the regression equation. Monte-Carlo method is also performed to compare the rejection power between each method. As the results, the probability plot Correlation Coefficient test which is derived in this study is better than the others. In particular, when sample size is small and distribution has the shape parameter, rejection power of probability plot Correlation Coefficient test considering the Coefficients of skewness is bigger than the others.
