Abstract.
A non-parametric method for the analysis of blocked factorial experiments, based on ranking within blocks, is proposed and shown to be equivalent to partitioning Friedman's test statistic into a set of contrasts reflecting polynomial components of the main effects and interaction. A slightly modified version of the procedure is suggested to partially overcome the problem of loss of power to detect one component when the model includes other components. This alternative procedure is shown to be equivalent to applying a standard normal theory analysis of variance to the ranks. The null distributions and power comparisons are investigated using simulation methods, and it is shown that the non-parametric methods are almost as powerful as the analysis of variance.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Author information
Authors and Affiliations
Additional information
Received: February 1999
Rights and permissions
About this article
Cite this article
Prescott, P., Shahlaee, R. The analysis of ranked data in blocked factorial experiments. Metrika 50, 37–54 (1999). https://doi.org/10.1007/s001840050034
Issue Date:
DOI: https://doi.org/10.1007/s001840050034