Model validation using equivalence tests

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Information theory and hypothesis testing: a call for pluralism (2005, methodology): “This approach of reversing hypotheses is the basis for equivalence tests ( Robinson & Froese 2004 ), more commonly employed in analyses of pharmaceutical trials and studies of environmental toxicology.”
Forest Growth and Yield Modeling (2011, methodology): “One alternative to these traditional statistical tests is the equivalence tests of Robinson and Froese (2004).”
Owl pellets: a more effective alternative to conventional trapping for broad‐scale studies of small mammal communities (2016, methodology): “TOST of equivalence identifies equivalence by rejecting the null hypothesis of dissimilarity when 95% confidence intervals fall within a specified range of similarity (i.e. 25% of the standard deviation; Cole & McBride 2004; Robinson & Froese 2004).”
Dynamic growth model for Scots pine (Pinus sylvestris L.) plantations in Galicia (north-western Spain) (2006, methodology): “In order to evaluate whether the model performs acceptably well when used for prediction of stand basal area and stand volume, a critical error, expressed as a percentage of the observed mean, was computed rearranging Freese’s (1960) χ2 n statistic (Reynolds, 1984; Robinson and Froese, 2004 ):”