Johnson Ching?Hong Li|Rory Waisman
Probability of bivariate superiority: A non-parametric common-language statistic for detecting bivariate relationships
University of Manitoba|University of Alberta
researchers often focus bivariate normal correlation r evaluate bivariate relationships however techniques assume linearity depend parametric assumptions propose new nonparametric statistical model intuitively understood conventional r probability bivariate superiority pbs development bp estimator pbs relationship extends dunlaps 1994 commonlanguage transformation r clr providing method directly estimate pbsthe probability x mean x paired score also mean probability superiority important form bivariate relationship could accurately estimated data met parametric assumptions r specify copula forms theoretical basis pbs provide algorithm estimating pbs sample describe results monte carlo experiment evaluated algorithm across 448 data conditions pbs estimate bp robust violations parametric assumptions offers useful method evaluating significance probabilityofsuperiority relationships bivariate data critical note bp estimates different form bivariate relationship r working examples show pbs effect significant absence significant correlation vice versa addition utilizing pbs model future research suggest new statistical procedure used find theoretically important previously overlooked effects past studies