Hi Steve, have you heard about Information-Theoretic Approach? It uses the
value of AIC (or AICc) to choose the best hypothesis among many a priori
hypothesis. In Anderson (2008) "Model Based Inference in the Life Sciences"
we see recomendations against stepwise (or all possible models) because
this can lead easily to spurious relations. The author recommend to create
several a priori hypothesis (models), using knowledge about the system and
then use the AICc to look for the best of them. Another thing that you have
to pay attention is the fact that you can not compare combinations of fixed
effects of class "mer" with REML = TRUE.

A hug

-- 
                                               Diego PJ

	[[alternative HTML version deleted]]

