On Fri, 30 Mar 2007, Jo?o Fadista wrote:
Dear all,
I would like to know if I can compare by a significance test 2 models
with different kind of parameters. Perhaps I am wrong but I think that
we can only compare 2 models if one is a sub model of the other.
The literature you seek is on '
Dear all,
I would like to know if I can compare by a significance test 2 models with
different kind of parameters. Perhaps I am wrong but I think that we can only
compare 2 models if one is a sub model of the other.
Med venlig hilsen / Regards
João Fadista
Ph.d. studerende / Ph.d. student
Hi,
I have 2 questions.
First - is it possible to use the offset term in a glmmPQL formula rather
than transforming the variables in the dataset beforehand?
Second - how do you compare the output/fit of 2 models produced through
glmmPQL if you can't use the Anova(model1, model2, tes
Another thought on checking the validity of the suggested
2*log(likelihood ratio) procedure I suggested: If it were my problem, I
think I would do some checking using Monte Carlo, e.g., as described in
sec. 2.6 of the vignette "MlmSoftRev" in the "mlmRev" package. This is
particular
You are correct on both counts. The exta line is inserted below;
obviously, I had it but failed to copy it into the email.
And you are also correct that one needs to be careful that both glm
and lmer are using comparable definitions for the log(likelihood). My
crude check
> ### To get around that, I computed 2*log(likelihood ratio) manually:
>
> lglk0 <- logLik(fit0)
> lglk.ID1. <- logLik(Fit.ID1.)
> pchisq(as.numeric(chisq.ID.), 1, lower=FALSE)
> > [1] 0.008545848
(I think you're missing a line in there)
But isn't this rather perilous unless you are confident th
It's not clear from your email what you tried, but "anova" to compare
two glmmPQL fits would not work for me. I switched to lmer and got
reasonable answers. The first includes what worked for me then what I
tried unsuccessfully with glmmPQL:
library(MASS) # for the "bacteria" data u
I use model comparison with glms without mixed effects with
anova(modelA,modelB),
with mixed effects glm (glmmPQL), this doesn't work. Is there a way to
compare model fits with glmmPQL's?
Paula M. den Hartog
Behavioural Biology
Institute of Biology Leiden
Leiden University
[[alternati
On 9/5/05, Thomas Petzoldt <[EMAIL PROTECTED]> wrote:
> Dear expeRts,
>
> there is obviously a general trend to use model comparisons, LRT and AIC
> instead of Wald-test-based significance, at least in the R community.
> I personally like this approach. And, when using LME's, it seems to be
> the
Dear expeRts,
there is obviously a general trend to use model comparisons, LRT and AIC
instead of Wald-test-based significance, at least in the R community.
I personally like this approach. And, when using LME's, it seems to be
the preferred way (concluded from postings of Brian Ripley and Dougla
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