Abstract
Recent work has shown that the rank transform methodology is flawed when applied to multifactor designs with interactions. A simple fix-up is proposed and shown to apply to designs typical of those found in agricultural research including split-plots. Simulation results suggest that the fix-up provides a valid procedure for analyzing multifactor designs when error distributions are symmetric or moderately skewed. The procedure appears to have power advantages over normal theory ANOVA when error distributions are heavy tailed.
Keywords
rank transform methodology
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Higgins, James J.; Blair, R. Clifford; and Tashtoush, Suleiman
(1990).
"THE ALIGNED RANK TRANSFORM PROCEDURE,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1443
THE ALIGNED RANK TRANSFORM PROCEDURE
Recent work has shown that the rank transform methodology is flawed when applied to multifactor designs with interactions. A simple fix-up is proposed and shown to apply to designs typical of those found in agricultural research including split-plots. Simulation results suggest that the fix-up provides a valid procedure for analyzing multifactor designs when error distributions are symmetric or moderately skewed. The procedure appears to have power advantages over normal theory ANOVA when error distributions are heavy tailed.
