Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ
Journal of Applied Statistics , Volume 47 - Issue 16 p. 2984- 3006
Bayesian inference for rank-order problems is frustrated by the absence of an explicit likelihood function. This hurdle can be overcome by assuming a latent normal representation that is consistent with the ordinal information in the data: the observed ranks are conceptualized as an impoverished reflection of an underlying continuous scale, and inference concerns the parameters that govern the latent representation. We apply this generic data-augmentation method to obtain Bayes factors for three popular rank-based tests: the rank sum test, the signed rank test, and Spearman's ρs.
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|Journal of Applied Statistics|
|Organisation||Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands|
van Doorn, J, Ly, A, Marsman, M, & Wagenmakers, E.-J. (2020). Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ. Journal of Applied Statistics, 47(16), 2984–3006. doi:10.1080/02664763.2019.1709053