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tips:model_selection_with_glmulti_and_mumin

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tips:model_selection_with_glmulti_and_mumin [2022/08/03 11:33] – Wolfgang Viechtbauertips:model_selection_with_glmulti_and_mumin [2022/08/03 12:51] – Wolfgang Viechtbauer
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 If we do want to make inferences about the various predictors, we may want to do so not in the context of a single model that is declared to be "best", but across all possible models (taking their relative weights into consideration). Multimodel inference can be used for this purpose. To get the glmulti package to handle ''rma.uni'' objects, we must register a ''getfit'' method for such objects. The necessary code for this comes with the metafor package, but it first needs to be evaluated with: If we do want to make inferences about the various predictors, we may want to do so not in the context of a single model that is declared to be "best", but across all possible models (taking their relative weights into consideration). Multimodel inference can be used for this purpose. To get the glmulti package to handle ''rma.uni'' objects, we must register a ''getfit'' method for such objects. The necessary code for this comes with the metafor package, but it first needs to be evaluated with:
-<code>+<code rsplus>
 eval(metafor:::.glmulti) eval(metafor:::.glmulti)
 </code> </code>
tips/model_selection_with_glmulti_and_mumin.txt · Last modified: 2022/10/13 06:07 by Wolfgang Viechtbauer