piecewiseSEM: Exploring Nature’s Complexity through Statistics

Post provided by Jonathan S. Lefcheck

Nature is complicated. As a scientist, you might say, “Well, duh,” but as students of nature, this complexity is probably the single greatest challenge we must face in trying to dissect the hows and whys of the natural world.

History is a Set of Lies Agreed Upon: Moving beyond ANOVA

For a long time, we tried to strip this complexity away by conducting very controlled experiments adhering to rigid designs. The ‘two-way fully-crossed analysis of variance’ will be familiar to anyone who has taken even the most basic stats class, because, for many decades, it was the gold standard for any experiment.

It might be tough to manipulate this whole reef.

The problem is: the real world doesn’t adhere to an ANOVA design. By this, I mean that by their very nature, manipulative experiments are artificial. It’s hard—if not impossible—to manipulate an entire forest or a coral reef, and as such, we retreat to more tractable, smaller investigations. There is certainly a lot of value in determining whether the phenomenon can occur, but these tightly regulated designs say nothing about whether they are likely to occur, particularly at the scales most relevant to humanity.

To get at the latter point, we must leave the safety of the greenhouse. However, our trusty ANOVA toolbox isn’t very useful anymore, because real-world data often violate the most basic statistical assumptions, not to mention the presence of numerous additional influences that may drive spurious relationships. Continue reading