[R] Question concerning anova()

[Bert Gunter]

Models with different fixed effects estimated by REML cannot be
compared by anova.

In future, please post questions on mixed effects models on the
r-sig-mixed-effects mailing lists. You're likely to receive more
informative replies there, too.

-- Bert

On Wed, Aug 22, 2012 at 7:23 AM, Rainer M Krug <r.m.krug at gmail.com> wrote:
> Hi
>
> I am comparing four different linear mixed effect models, derived from
> updating the original one. To compare these, I want to use anova(). I
> therefore do the following (not reproducible - just to illustration
> purpose!):
>
> dat <- loadSPECIES(SPECIES)
> subs <- expression(dead==FALSE & recTreat==FALSE)
> feff <- noBefore~pHarv*year      # fixed effect in the model
> reff <- ~year|plant              # random effect in the model, where year is
> the
> corr <- corAR1(form=~year|plant) # describing the within-group correlation
> structure
> #
> dat.lme <- lme(
>              fixed = feff,                           # fixed effect in the
> model
>              data  = dat,
>              subset = eval(subs),
>              method = "ML",
>              random = reff,                          # random effect in the
> model
>              correlation = corr,
>              na.action = na.omit
>              )
> dat.lme.r1 <- update(dat.lme, random=~1|plant)
> dat.lme.f1 <- update(dat.lme, fixed=noBefore~year)
> dat.lme.r1.f1 <- update(dat.lme.r1, fixed=noBefore~year)
>
>
> The anova is as follow:
>
>> anova(dat.lme, dat.lme.r1, dat.lme.f1, dat.lme.r1.f1)
>               Model df      AIC      BIC    logLik   Test      L.Ratio
> p-value
> dat.lme           1  9 1703.218 1733.719 -842.6089
> dat.lme.r1        2  7 1699.218 1722.941 -842.6089 1 vs 2 1.019230e-07
> 1
> dat.lme.f1        3  7 1705.556 1729.279 -845.7779
> dat.lme.r1.f1     4  5 1701.556 1718.501 -845.7779 3 vs 4 8.498318e-08
> 1
>
> I have two questions:
> 1) I am wondering why the "2 vs 3" does not give the Test values?
> Is this because the two models are considered as "identical", which would be
> strange, due to the different logLik values.
>
> 2) If I want to compare all models among each other - is there a "best" way?
> I would be reluctant to do several ANOVA's, due to necessary corrections for
> multple tests (although this should not be a problem here?)
>
> I can obviously select the best model based on the AIC.
>
> Thanks in advance,
>
> Rainer
>
> --
> Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
> UCT), Dipl. Phys. (Germany)
>
> Centre of Excellence for Invasion Biology
> Stellenbosch University
> South Africa
>
> Tel :       +33 - (0)9 53 10 27 44
> Cell:       +33 - (0)6 85 62 59 98
> Fax :       +33 - (0)9 58 10 27 44
>
> Fax (D):    +49 - (0)3 21 21 25 22 44
>
> email:      Rainer at krugs.de
>
> Skype:      RMkrug
>
> ______________________________________________
> R-help at r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.



-- 

Bert Gunter
Genentech Nonclinical Biostatistics

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