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[R-meta] variable importance in the context of meta-analysis

Wolfgang Viechtbauer 
Dear Diego,

Yes, this makes sense. The Akaike weight of a model is the estimated probability that the model is the best model (in the sense of how 'best' is defined under such an information-theoretic approach) in the candidate set. So, by adding up the weights for all models that contain the predictor of interest, you get, roughly speaking, the probability that the predictor is relevant.

As references, you could take a look at the book "Model Selection and Multimodel Inference" by Burnham and Anderson or the somewhat shorter/condensed "Model Based Inference in the Life Sciences: A Primer on Evidence" by Anderson.

Best,
Wolfgang

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Diego Grados Bedoya variable importance in the context of meta-analysis Sep 17 Wolfgang Viechtbauer variable importance in the context of meta-analysis Sep 18