[R] Urgent - I really need some help lme4 model avg Estimates

[Dragonwalker]

I understand where you are coming from, but the issue is that some
exploration of the data through graphs and the like, showed that patterns
could be seen. However with only 7 means it is extremely difficult to get
any kind of statistical evidence and as some mean values are the same some
of the tests that I wanted to use such as a Mann-Whitney would not even run
so I had to resort to a one-sample Wilcoxon with a set mu value. (minimum
p-value that was even possible was p=0.280). 

I asked a couple of forums in December about the issues at hand and they
suggested that I look into mixed-effect models so I read some chapters on
them and got very excited, but at the time still thought of them as some
test that could give me means. However it all clicked and I realise that
they can be more useful as a tool to illustrate which factors and covariates
best fit to the response variable.

I understand the concepts of fitting an intercept and slope somewhat but the
paperwork on it can be a little confusing, however the way they were used in
the paper (of which I attached one of the tables) seemed a very
straightforward method of teasing the intricate factors of habitat, age and
other factors that could be affecting behaviour such as time feeding and
foraging rate. Believe me, if i could have survived with Kruskal-Wallis then
I would have had my thesis written up three months ago with a lot less
stress. I am not looking for pretty as I don't even want it published, but I
did hope to be able to give the time that I spent collecting data justice.

I have come really far, thanks to some great people, but I do not have
anyone near me who can help and my adviser is 3000 miles away too and is not
a statistician either.
All I would like to know is how could Maslo et al. have calculated estimates
for all categories AND an intercept and is there a method to do this in R. 
I have spent months trying to find these answers and so I would greatly
appreciate an answer to this question. 

Thank you again.



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