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Robustness and monotonicity properties of generalized correlation coefficients
Authors:Vivian Yi-Ju ChenVernon M Chinchilli  Donald St P Richards
Institution:a Department of Statistics, Tamkang University, Tamsui, Taipei 251, Taiwan, ROC
b Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, PA 17033, United States
c Department of Statistics, The Pennsylvania State University, University Park, PA 16802, United States
Abstract:A new class of generalized correlation coefficients that contains the Pearson and Kendall statistics as special cases was defined by Chinchilli et al. (2005) and applied to the estimation of correlations coefficients within the context of 2×2 cross-over designs for clinical trials. In this paper, we determine the infinitesimal robustness and local stability properties of these generalized correlation coefficients by deriving their corresponding influence functions. For cases in which the population distribution is a bivariate normal or a mixture of bivariate normal distributions we obtain explicit formulas, and establish monotonicity and sign-reverse rule properties of the generalized correlation coefficients.
Keywords:Clinical trials  Correlation coefficient  Cross-over design  Influence function  Robustness  Strictly sign regular kernel
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