[R] MuMIn Problem getting adjusted Confidence intervals

[Kamil Bartoń]

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-request w r-project.org pisze:
> Message: 42
> Date: Mon, 29 Aug 2011 08:28:22 -0700 (PDT)
> From: Marcos Lima<robalinho.lima w googlemail.com>
> To:r-help w r-project.org
> Subject: [R] MuMIn Problem getting adjusted Confidence intervals
> Message-ID:<1314631702645-3776500.post w 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