Comparing nonparametric tests of equality of means for randomized block designs

Authors

Donald J. Best, University of NewcastleFollow
J. C. W Rayner, University of WollongongFollow
Olivier Thas, University of WollongongFollow
Jan De Neve, Ghent University
David Allingham, University of Newcastle

RIS ID

100363

Publication Details

Best, D. J., Raynor, J. C. W., Thas, O., De Neve, J. & Allingham, D. (2016). Comparing nonparametric tests of equality of means for randomized block designs. Communications in Statistics: Simulation and Computation, 45 (5), pp. 1718-1730.

Abstract

A number of nonparametric tests are compared empirically for a randomized block layout. We assess tests appropriate for when the data are not consistent with normality or when outliers invalidate traditional ANOVA tests. The objective is to assess, within this setting, tests that use ranks within blocks, the rank transform procedure that ranks the complete sample and continuous analogues of the Cochran-Mantel-Haenszel tests. The usual linear model is assumed, and our primary foci are tests of equality of means and component tests that assess linear and quadratic trends in the means. These tests include the traditional Page and Friedman tests. We conclude that the rank transform tests have competitive power and warrant greater use than is currently apparent.