In my thesis data set, I'm trying to sort out which years were poor and which were good based on an assortment of breeding bird metrics. The one I'm currently looking at is clutch size, where I've converted 1 and 2 egg clutches (this species never lays more) to a binomial distribution. I ran a glm that looked like this, in brief:

model1<-glm(Clsz~Year)

I then ran Tukey's comparisons from the multcomp package, and asked for confidence intervals:

BTWNyrs<-glht(model1, linfct=mcp(Year = "Tukey"))

confint(BTWNyrsMSI)

par(mfrow=c(1,1))

plot(print(confint(BTWNyrsMSI)))

Two problems I'm having: though I understand the concept of confidence intervals, I don't understand what this output is showing me. It looks to be giving some sort of interval between each pairing of years possible

View attachment 1344

How can I interpret this?

In Sigmaplot, I've made a bar chart with the means of each year, and error bars showing confidence intervals. If this was a normal distribution, these would be ok, right? However, because the data are binomial, I'm assuming these confidence intervals are not correct?

View attachment 1345

Is there a way of generating confidence intervals for each year that I can save and use to create a bar chart like the Sigmaplot one? I'd like this both for comparing non-overlapping CIs to get a sense of what's what, but also for including in my thesis.

Thanks for any help!!

Mog