, Volume 65, Issue 1, pp 57-68
Date: 18 Aug 2010

Issues in information theory-based statistical inference—a commentary from a frequentist’s perspective

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Abstract

After several decades during which applied statistical inference in research on animal behaviour and behavioural ecology has been heavily dominated by null hypothesis significance testing (NHST), a new approach based on information theoretic (IT) criteria has recently become increasingly popular, and occasionally, it has been considered to be generally superior to conventional NHST. In this commentary, I discuss some limitations the IT-based method may have under certain circumstances. In addition, I reviewed some recent articles published in the fields of animal behaviour and behavioural ecology and point to some common failures, misunderstandings and issues frequently appearing in the practical application of IT-based methods. Based on this, I give some hints about how to avoid common pitfalls in the application of IT-based inference, when to choose one or the other approach and discuss under which circumstances a mixing of the two approaches might be appropriate.

Communicated by L. Garamszegi
This contribution is part of the Special Issue ‘Model selection, multimodel inference and information-theoretic approaches in behavioural ecology’ (see Garamszegi 2010).