%0 Journal Article
%T Effective Analysis of Interactive Effects with Non-Normal Data Using the Aligned Rank Transform, ARTool and SAS£¿ University Edition
%A Edward Durner
%J Horticulturae | An Open Access Journal from MDPI
%D 2019
%R https://doi.org/10.3390/horticulturae5030057
%X Most statistical techniques commonly used in horticultural research are parametric tests that are valid only for normal data with homogeneous variances. While parametric tests are robust when the data ¡®slightly¡¯ deviate from normality, a significant departure from normality leads to reduced power and the probability of a type I error increases. Transformations often used to normalize non-normal data can be time consuming, cumbersome and confusing and common non-parametric tests are not appropriate for evaluating interactive effects common in horticultural research. The aligned rank transformation allows non-parametric testing for interactions and main effects using standard ANOVA techniques. This has not been widely adapted due to its rigorous mathematical nature, however, a downloadable (ARTool) is now available, which performs the math needed for the transformation. This study provides step-by-step instructions for integrating ARTool with the free edition of SAS (SAS University Edition) in an easily employed method for testing normality, transforming data with aligned ranks, and analysing data using standard ANOVAs. View Full-Tex
%U https://www.mdpi.com/2311-7524/5/3/57