A few thoughts:

* your data didn't make it through to the list as far as I can see -- any
chance you can post it somewhere (or send it to me)?
* have you explored your data graphically to see what's going on with Day?
* we know that Gamma models are somewhat fragile (it will be good to try
this example out to make them more robust); if you don't have a strong
attachment to Gamma (for theoretical or cultural reasons), it is often
practically easier to do log-Normal rather than Gamma models (i.e. take
logs of the response variable and fit a LMM).  (McCullagh and Nelder talk
about this issue a little bit in their GLM book.)

Less important:

* Round/Tank/Pair/Fish (four levels of nested variation) looks like a
pretty complicated random effects specification: do you have enough data to
fit that many random effects?

Even less important:

* in the R formula syntax, Treatment + Day + Treatment*Day is equivalent to
just Treatment*Day (or Treatment + Day + Treatment:Day)


On Tue, Aug 5, 2014 at 10:11 AM, Kirsty McLaughlin <kmclaughlin23@qub.ac.uk>
wrote:

>
> To whom it may concern,
>
>
> I am a novice in the use of R, however I have been trying my best to
> assess the effect of noise treatment over a three day period on the time
> spent carrying out certain behaviours. I am using a GLMM as I don't have
> sample independence and my response variables are non-normally distributed
> and skewed. I have been using Family Gamma for my analysis.
>
>
> When running a model on 'TTAgressionCon' (time spent being aggressive)
> including the predictor variable Day (3 levels) I get the above error
> message. When the model runs with other predictor variables e.g. Gender, I
> do not get this error.
>
>
> I have the most up to date version of lme4.
>
>
> Below is the model that generated the error message:
>
> model1 <- glmer(TTAggressionCon ~ Treatment + Day + Treatment*Day +
> (1|Round/Tank/Pair/Fish), data = data1, family = Gamma)
>
>
> I have attached my data if this helps with diagnosis or suggestions.
>
>
> Any help or guidance on this matter would be greatly appreciated.
>
>
>
> Kind regards
> Kirsty McLaughlin
>
> PhD student
> Queen's University Belfast
> School of Biological Sciences
> Medical Biology Centre
> 97 Lisburn Road
> Belfast, BT9 7GT
>
> Tel: 028 90 972103
> Email: kmclaughlin23@qub.ac.uk
> Web: www.animal-behaviour.eu<http://www.animal-behaviour.eu>
>
>
> _______________________________________________
> R-sig-mixed-models@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>

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