[R] Using MuMIn - error message

[Dunbar, Michael J.]

Hi Rachel

Do you accidentally have nlme and lme4 loaded at the same time? If so then try unloading nlme.

regards
Mike
 
________________________________________
From: r-help-bounces at r-project.org [r-help-bounces at r-project.org] On Behalf Of Dragonwalker [dragonwalkerart at hotmail.com]
Sent: 23 March 2012 21:55
To: r-help at r-project.org
Subject: [R] Using MuMIn - error message

Hello,
I hope that you can bare with me. I am new to models, but I think I have a
pretty godd understanding of how to run them now, including how to use AICc
and Anova. The issue is that I have many factors that I wish to compare so
doing each one at a time would take forever.
I came across the MuMIn package and I was so excited, however I am getting
an error message and i don't know why.
Firstly it is a mixed model that I am running with lme4. The .csv file that
it comes from has more factors than I will probably use but I only listed
the ones that I wanted to test. I had also coded the ones that are labels
and not continuous data using the as.factor command and I ran the most
complex model and ran summary() and it seemed to have worked fine.

My model was:
fm2test<-lmer(Feeding~MF.vs.OF+Age.class+tide.h.l+Site+HDp+(1|Brood),
data=ABMtest.df)

and then I wanted to use the dredge command as so:
dd<-dredge(fm2test, trace=TRUE, rank="AICc", REML=FALSE)

I got an error:
Error in UseMethod("fixef") :
  no applicable method for 'fixef' applied to an object of class "mer"

I have no idea how to fix this. I have looked at ?dredge but cannot find
anything there and I am very new to R so any help would be greatly
appreciated.

I want to run all the possible models using the factors and then want to
identify those models which best explain Feeding. I also have other models
to run and in addition I have more factors to use but wanted to do this
first as a test.

Could someone also advise me on a way to list all models in order and if
each model is accessible in order to compare with Anova?

Thank you so much in advance.

Rachel

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