Beyond differences in means: robust graphical methods to compare two groups in neuroscience

作者：Rousselet Guillaume A^*; Pernet Cyril R; Wilcox Rand R

来源：European Journal of Neuroscience, 2017, 46(2): 1738-1748.

DOI：10.1111/ejn.13610

• data visualisation
• difference asymmetry function
• quantile estimation
• robust statistics
• shift function

If many changes are necessary to improve the quality of neuroscience research, one relatively simple step could have great pay-offs: to promote the adoption of detailed graphical methods, combined with robust inferential statistics. Here, we illustrate how such methods can lead to a much more detailed understanding of group differences than bar graphs and t-tests on means. To complement the neuroscientist's toolbox, we present two powerful tools that can help us understand how groups of observations differ: the shift function and the difference asymmetry function. These tools can be combined with detailed visualisations to provide complementary perspectives about the data. We provide implementations in R and MATLAB of the graphical tools, and all the examples in the article can be reproduced using R scripts.

• 出版日期2017-7