[R] MuMIn - assessing variable importance following model averaging, z-stats/p-values or CI?

[Robertson, Andrew]

Dear R users,

Recent changes to the MuMIn package now means that the model averaging command (model.avg) no longer returns confidence intervals, but instead returns zvalues and corresponding pvalues for fixed effects included in models.

Previously I have used this package for model selection/averaging following Greuber et al (2011) where it suggests that one should use confidence intervals from model averaging to assess whether your fixed effects have an affect or not  (If confidence intervals do not span zero then variable has an affect).

Can anyone tell me why MuMIn now gives z-stats and p-values and whether these should be used to assess the 'significance'/importance of variables when model averaging?

Heres the example code of what I'm doing....

#-------------------------------------------------------------------------------------#
ps<-lmer(tranPS~(
    Sex+
    Age.Cat2+
    TOTAL+
    Propfarm+
    Maize+
    TOTAL:Propfarm+
    Maize:TOTAL+
    Maize:Propfarm+
    (1|Socialgroup)+(1|Year)+(1|Tattoo)),REML=FALSE, data=propspec)

pss<-standardize(ps,standardize.y = FALSE)

psdrg<-dredge(pss)

summary(model.avg(get.models(psdrg,subset=delta<2)))
#-------------------------------------------------------------------------------------#

REf -Grueber, C.E., Nakagawa, S., Laws, R.J. & Jamieson, I.G. (2011) Multimodel inference in ecology and evolution: challenges and solutions. Journal of evolutionary biology, 24, 699-711.

Any help would be much appreciated

Regards

Andrew Robertson
PhD student
Centre for Ecology and Conservation
University of Exeter, Cornwall Campus
Tremough, Cornwall. TR10 9EZ
UK
Tel: 01326 371852
Email: ar313 at exeter.ac.uk
Web page: http://biosciences.exeter.ac.uk/staff/postgradresearch/andrewrobertson/