A Bayesian analysis for the Wilcoxon signed-rank statistic. Issue 21 (2nd November 2018)

• Record Type: Journal Article
• Authors: Chechile, Richard A.
• Is Part Of: Communications in statistics. Volume 47:Issue 21(2018)
• Page Start: 5241
• Page End: 5254
• Publication Date: 2018-11-02
• Subjects: Bayesian analysis -- Non parametric statistics -- Robust inference -- Wilxoxon signed-rank statistic; 62C10 -- 62F15 -- 62F35 -- 62G86; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2017.1388402
• Languages: English
• ISSNs: 0361-0926

Abstract

ABSTRACT: A Bayesian analysis is provided for the Wilcoxon signed-rank statistic ( T + ). The Bayesian analysis is based on a sign-bias parameter φ on the (0, 1) interval. For the case of a uniform prior probability distribution for φ and for small sample sizes (i.e., 6 ⩽ n ⩽ 25), values for the statistic T + are computed that enable probabilistic statements about φ. For larger sample sizes, approximations are provided for the asymptotic likelihood function P ( T + |φ) as well as for the posterior distribution P (φ| T + ). Power analyses are examined both for properly specified Gaussian sampling and for misspecified non Gaussian models. The new Bayesian metric has high power efficiency in the range of 0.9–1 relative to a standard t test when there is Gaussian sampling. But if the sampling is from an unknown and misspecified distribution, then the new statistic still has high power; in some cases, the power can be higher than the t test (especially for probability mixtures and heavy-tailed distributions). The new Bayesian analysis is thus a useful and robust method for applications where the usual parametric assumptions are questionable. These properties further enable a way to do a generic Bayesian analysis for many non Gaussian distributions that currently lack a formal Bayesian model.