sodiumfish wrote:
I have run a glm with a final formula of : (dependent variable = parasite
load, main effects are sex, month, length and weight, with sex:month and
length:weight first order interactions).
I am using the summary(mod) command to give me the contrasts, which I
believe use the contr.treatment command. I do not have a treatment group
as such as I am comparing data from a wild system so I use the relevel
command to reorder my factors in order to check the difference between
each level and every other. I then use the coefficients and their related
p-values to assess whether each level of my factors is significantly
different from the next. This is fine for most things but what I really
want to do is to assess whether there is a significant difference of
between males and females in any particular month. However, because of my
interaction term the male and female for any particular month are always
the missing coefficients and so I can't contrast them with one another.
Is there a way (preferably a relatively simple way) for me to do this. You
will probably realise from my description above that I am a biologist not
a statistician, so if anyone can help me in plain English that would be an
enormous help.
It would be a little easier if you gave us a reproducible example.
It sounds like the easiest thing to do would be to partition your data set
by month and run separate models in each month. If you were running
lm() rather than glm() you could use lmList from the nlme package, but
instead you should look at:
http://finzi.psych.upenn.edu/Rhelp08/2008-February/154519.html
for a solution.
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