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The models' selection was based on the Akaike Criterion AICC), the Bayesian Information Criteron (BIC) and log-likelihood, incorporating clinical knowledge.
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Backward model selection was performed to select risk factors for the final model.
Our model selection was based on average loss.
Model selection was conducted by using Bayesian information criterion based forward stepwise selection.
Hence all further model selection was restricted to plot level mixed models.
Model selection was based on optimization of Akaike's information criterion (AIC) (Akaike 1973).
Model selection was made choosing the covariance structure with the lowest Akaike information criteria.
Thus, stepwise model selection was then repeated for all remaining variables.
Model selection was based on a fitness which penalized models for increasing complexity.
Bayesian model selection was used to identify the intrinsic (within-source) and extrinsic (between-source) connectivity.
Oh, and the model selection was impeccable.
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