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The primary basis given for this restriction was to achieve better fitting models and statistically significant E-R trends.
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The context-dependent acoustic models provide better fitting modeling and this is shown by the consistent increase in the results.
Fitting a spatial component to the error variance, as we have done here, has been found to give better fitting models for many forestry trials and traits than when modelling only replicate and block effects (Dutkowski et al. [2002], [2006]; Dungey et al. [2012]).
A process-based approach where outcomes are modelled as a function of distance to the event that is most associated with the changes observed (for example, time to dementia diagnosis) has been shown to result in a reduction of residual variance estimates and better fitting models [ 32].
26 The AIC, BIC and SSABIC indicate relative goodness of fit; lower values represent better fitting models.
Lower AIC and BIC values suggest better fitting models.
The AIC is a relative measure of information lost when fitting the model; hence, smaller AIC values suggest better fitting models.
Differences in BIC can be used to compare competing models, with better fitting models having smaller BIC values.
Lower values reflect better fitting models.
To assess the relative fit of each model, we compared the Akaike's Information Criteria (AIC), with better fitting models having lower AIC [ 31].
According to guidelines [ 28], better fitting models are accepted when the change in the RMSEA (∆RMSEA) is equal or greater than 0.01.
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