March 1, 2014 Journal article Open Access

Murtaugh, Paul A.

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    <subfield code="a">Statistical hypothesis testing has been widely criticized by ecologists in recent
years. I review some of the more persistent criticisms of P values and argue that most stem
from misunderstandings or incorrect interpretations, rather than from intrinsic shortcomings
of the P value. I show that P values are intimately linked to confidence intervals and to
differences in Akaike's information criterion (DAIC), two metrics that have been advocated as
replacements for the P value. The choice of a threshold value of DAIC that breaks ties among
competing models is as arbitrary as the choice of the probability of a Type I error in
hypothesis testing, and several other criticisms of the P value apply equally to DAIC. Since P
values, confidence intervals, and DAIC are based on the same statistical information, all have
their places in modern statistical practice. The choice of which to use should be stylistic,
dictated by details of the application rather than by dogmatic, a priori considerations.</subfield>
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    <subfield code="a">10.1890/13-0590.1</subfield>
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    <subfield code="a">In defense of P values</subfield>
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