Hi Marcos,
The 'adjusted CI' (based on the 'adjusted se estimator' as in section 4.3.3 of Burnham & Anderson
2002) cannot be calculated for 'lmer' model because it does not give df's for the coefficients.
kamil
Dnia 2011-08-30 12:00, r-help-requ...@r-project.org pisze:
Message: 42
Date: Mon, 29 Aug 2011 08:28:22 -0700 (PDT)
From: Marcos Lima<robalinho.l...@googlemail.com>
To:r-help@r-project.org
Subject: [R] MuMIn Problem getting adjusted Confidence intervals
Message-ID:<1314631702645-3776500.p...@n4.nabble.com>
Content-Type: text/plain; charset=UTF-8
Hello R users
I'm using MuMIn but for some reason I'm not getting the adjusted confidence
interval and uncoditional SE whe I use model.avg().
I took into consideration the steps provided by Grueber et al (2011)
Multimodel inference in ecology and evolution: challenges and solutions in
JEB.
I created a global model to see if malaria prevalence (binomial
distribution) is related to any life history traits of 14 different birds
species, while controling for Family and genus in a GLMM:
global.model.Para<-lmer(cbind(Parahaemoproteus,FailPh)~factor(SS)+factor(NT)+NH+W+IT+factor(MS)+(1|Family/Genus),family=binomial,data=malaria)
I than standardize the input variables using the function standardize form
the arm package:
stdz.model.Para<-standardize(global.model.Para,standardize.y=FALSE)
But I get this message:
Warning messages lost:
In is.na(thedata):
is.na() aplied to an object different from list or vector of type "Null"
I then proceed to use the dredge fucntion:
model.set.Para<-dredge(stdz.model.Para)
<...>
top.models.Para<-get.models(model.set.Para,subset=delta<=7)
top.models
But when I do the model average I do not seem to be getting the variance or
Uncoditional SE and I'm guessing that the Confidence interval are no
conditional either:
model.avg(top.models.Para,method="NA")
<...>
Averaged model parameters:
Coefficient SE Lower CI Upper CI
(Intercept) -4.75 1.410 -7.510 -1.9900
factor(MS)1 -1.54 0.809 -3.120 0.0471
factor(NT)1 2.28 1.310 -0.286 4.8500
factor(SS)1 3.30 0.968 1.400 5.2000
z.IT -2.79 2.230 -7.160 1.5800
z.NH 2.28 1.660 -0.968 5.5300
z.W -1.74 1.490 -4.650 1.1800
Confidence intervals are unadjusted
Relative variable importance:
factor(SS) factor(MS) z.NH z.IT z.W factor(NT)
0.82 0.33 0.32 0.20 0.07 0.01
Does anyone know what I might be doing wrong?
thanks for the help
Marcos
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