Thanks Kingsford... that does the trick perfectly!
Simon
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See ?par and note the 'mar' parameter
Here's an example:
library(multcomp)
labs <- c('short', 'medium', 'long')
treatment <- gl(3, 10, labels = labs)
response <- rnorm(30, mean=as.numeric(treatment))
mult <- glht(lm(response ~ treatment),
linfct=mcp(treatment='Means'))
par(mar=c(
Dear R-users,
I'm currently using the multcomp package to produce plots of means with 95%
confidence intervals
i.e.
mult<-glht(lm(response~treatment, data=statdata),
linfct=mcp(treatment="Means"))
plot(confint(mult,calpha = sig))
Unfortunately the y-axis on the plot appears to be fixed and henc
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