I was reading a paper this morning. It included a perversion of a common statistical analysis that is fundamentally wrong, utterly unneccesary, and has an easy solution. This perversion, unfortunately, is also distressingly common. Inspired by O’Hara and Kotze’s 2010 paper Do Not Log-Transform Count Data, I now offer you this blog post/rant, entitled “Do not flip-flop variables to make them work in your #@%*^& ANOVA.”
What set me off was a statement about the presence or absence of a particular fish in alpine lakes (details have been blurred to protect the guilty):
Lakes containing [fish] were lower in elevation…than lakes without [fish].
This statement was followed by the results of a non-parametric ANOVA confirming that lakes with fish were at significantly lower elevations than lakes without them. Can you spot the problem here? This model implies–wait for it–that you can flatten mountain ranges by adding fish to their lakes. Who knew?