The rank-based association between two variables can be modeled by introducing a latent normal level to ordinal data. We demonstrate how this approach yields Bayesian inference for Kendall's τ, improving on a recent Bayesian solution based on its asymptotic properties.

Additional Metadata
Keywords Rank correlation, Semi-parametric inference
Persistent URL dx.doi.org/10.1016/j.spl.2018.10.004
Journal Statistics & Probability Letters
Citation
van Doorn, J, Ly, A, Marsman, M, & Wagenmakers, E.-J. (2019). Bayesian estimation of Kendall's τ using a latent normal approach. Statistics & Probability Letters, 145, 268–272. doi:10.1016/j.spl.2018.10.004