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      Similarities in dance follower behaviour across honey bee species suggest a conserved mechanism of dance communication

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      Animal Behaviour
      Elsevier BV

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          glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling

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            Data Structures for Statistical Computing in Python

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              AIC model selection using Akaike weights.

              The Akaike information criterion (AIC; Akaike, 1973) is a popular method for comparing the adequacy of multiple, possibly nonnested models. Current practice in cognitive psychology is to accept a single model on the basis of only the "raw" AIC values, making it difficult to unambiguously interpret the observed AIC differences in terms of a continuous measure such as probability. Here we demonstrate that AIC values can be easily transformed to so-called Akaike weights (e.g., Akaike, 1978, 1979; Bozdogan, 1987; Burnham & Anderson, 2002), which can be directly interpreted as conditional probabilities for each model. We show by example how these Akaike weights can greatly facilitate the interpretation of the results of AIC model comparison procedures.
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                Journal
                Animal Behaviour
                Animal Behaviour
                Elsevier BV
                00033472
                November 2020
                November 2020
                : 169
                : 139-155
                Article
                10.1016/j.anbehav.2020.09.011
                afb9953c-c43c-4685-b086-c13e1e0d0c5d
                © 2020

                https://www.elsevier.com/tdm/userlicense/1.0/

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