[R] Error in MuMIn "models are not all fitted to the same data"

[Kamil Bartoń]

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 <k.barton w abdn.ac.uk
> <mailto:k.barton w 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-request w r-project.org
>     <mailto:r-help-request w r-project.org> wrote:
>
>         Message: 56
>         Date: Thu, 14 Nov 2013 18:01:27 -0800
>         From: Lilly Dethier<lillydethier w gmail.com
>         <mailto:lillydethier w gmail.com>__>
>         To:r-help w r-project.org <mailto:To%3Ar-help w r-project.org>
>         Subject: [R] Error in MuMIn "models are not all fitted to the same
>                data"
>         Message-ID:
>
>         <CAOK+e=Z_0pMEFKdPxZ5Eub+__DYhHFjzGk3Lcqczsa9TimAP4n_w w __mail.gmail.com
>         <mailto:Z_0pMEFKdPxZ5Eub%2BDYhHFjzGk3Lcqczsa9TimAP4n_w w 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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