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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 based on optimization of Akaike's information criterion (AIC) (Akaike 1973).
Model selection was conducted by using Bayesian information criterion based forward stepwise selection.
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.
Hence all further model selection was restricted to plot level mixed models.
Oh, and the model selection was impeccable.
Model selection was done using jMODELTEST [39].
Model selection was based on Akaike's information criterion (AIC) and likelihood ratio test [11].
Model selection was carried out using Akaike's Information Criterion (AIC) [29] and analysis of deviance.
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