It's the (typical) na.action = na.omit problem. You have missing values
in your data, so the number of observations differs between models using
different variables.
BTW with the recent lme4 package, your code throws a lot of warnings
about the use of lmer with non-gaussian family and ignored REML
argument. Also, consider using "update" rather than rewriting the models
each time.
kamil
On 2013-11-15 17:10, Lilly Dethier wrote:
Of course! Here's my data file and R code file. Thanks so much for your
help!!
Lilly Dethier
On Fri, Nov 15, 2013 at 8:14 AM, Kamil Bartoń mailto:k.bar...@abdn.ac.uk>> wrote:
works ok with mock-up data. Can you give some code to reproduce this
error?
kamil
On 2013-11-15 11:00, r-help-requ...@r-project.org
<mailto:r-help-requ...@r-project.org> wrote:
Message: 56
Date: Thu, 14 Nov 2013 18:01:27 -0800
From: Lilly Dethiermailto:lillydeth...@gmail.com>__>
To:r-help@r-project.org <mailto:to%3ar-h...@r-project.org>
Subject: [R] Error in MuMIn "models are not all fitted to the same
data"
Message-ID:
mailto:z_0pmefkdpxz5eub%2bdyhhfjzgk3lcqczsa9timap4...@mail.gmail.com>>
Content-Type: text/plain
I'm pretty new to GLMMs and model averaging, but think I'm
getting some
understanding of it all through lots of reading. However, I keep
receiving
an error message when trying to average models that I don't
understand and
can't find any resources about. I'm doing science education
research trying
to evaluate population demographic factors that predict biology
student
math performance. I have a lot of factors and so I tested a lot
of models.
6 of my models had pretty similar AIC values (and evidence
ratios of less
than 2.7) so I'm trying to average them. I keep receiving an
error message
that says the models are not fitted to the same data, but I have
no idea
how this is possible because all the models are from the same
set of data
(same file and same variables)...strangely it seems to work when
I try to
average MEx7, MEx10, & MEx22 only OR MEx24, MEx29, and MEx47
only. My code
is below. Any ideas? Thanks for any advice you can offer!!
library(MuMIn)
MEx7=lmer(cbind(c.score, w.score) ~ year + transfer + gender +
p.math +
(1|section) + (1|quarter), family=binomial, data=survey.full,
REML=F)
MEx10=lmer(cbind(c.score, w.score) ~ transfer + gender + p.math
+ Pmajor +
(1|section) + (1|quarter), family=binomial, data=survey.full,
REML=F)
MEx22=lmer(cbind(c.score, w.score) ~ year + transfer + p.math +
(1|section)
+ (1|quarter), family=binomial, data=survey.full, REML=F)
MEx24=lmer(cbind(c.score, w.score) ~ transfer + gender + p.math +
(1|section) + (1|quarter), family=binomial, data=survey.full,
REML=F)
MEx29=lmer(cbind(c.score, w.score) ~ transfer + p.math + Pmajor +
(1|section) + (1|quarter), family=binomial, data=survey.full,
REML=F)
MEx47=lmer(cbind(c.score, w.score) ~ transfer + p.math +
(1|section) +
(1|quarter), family=binomial, data=survey.full, REML=F)
MExAvg=model.avg(rank=AIC, MEx24, MEx7, MEx10, MEx47, MEx29, MEx22)
Error in model.avg.default(rank = AIC, MEx24, MEx7, MEx10,
MEx47, MEx29, :
models are not all fitted to the same data
Lilly Dethier
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