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Simplicity and complexity in ecological data analysis
1Department of Statistics, Oregon State University, Corvallis, Oregon 97331, USA. murtaugh@science.oregonstate.edu
Abstract:
I argue that ecological data analyses are often needlessly complicated, and I present two examples of published analyses for which simpler alternatives are available. Unnecessary complexity is often introduced when analysts focus on subunits of the key experimental or observational units in a study, or use a very general framework to present an analysis that is a simple special case. Simpler analyses are easier to explain and understand; they clarify what the key units in a study are; they reduce the chances for computational mistakes; and they are more likely to lead to the same conclusions when applied by different analysts to the same data.
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