In spite of the wide use and acceptance of information theoretic approaches in the wildlife sciences, debate continues on the correct use and interpretation of Akaike's Information Criterion as compared to frequentist methods. Misunderstandings as to the fundamental nature of such comparisons continue. Here we agree with Steidl's argument about situation-specific use of each approach. However, Steidl did not make clear the distinction between statistical and biological hypotheses. Certainly model selection is not statistical, or null, hypothesis testing; importantly, it represents a more effective means to test among competing biological, or research, hypotheses. Employed correctly, it leads to superior strength of inference and reduces the risk that favorite hypotheses are uncritically accepted.
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1 September 2007
Statistical Versus Biological Hypothesis Testing: Response to Steidl
D.J.H. SLEEP,
M.C. DREVER,
T.D. NUDDS
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Journal of Wildlife Management
Vol. 71 • No. 7
September 2007
Vol. 71 • No. 7
September 2007
Akaike's Information Criterion
biological hypothesis
frequentist
hypothesis testing
information theoretic approach
statistical hypothesis