You could also use lattice + Hmisc:
# Fake data (taken from Dennis Murphy's reply):
mortrate <- round(runif(100), 3)
moe = 1.96 * sqrt(mortrate * (1 - mortrate))/10
dd <- data.frame(rate = mortrate, CI.lower = mortrate - moe, CI.upper =
mortrate + moe, hosp = factor(paste('H', 1:100, sep = '')))
Hi:
Following up on Ben's suggestion re ggplot2, here's a manufactured example:
# Fake data:
mortrate <- round(runif(100), 3)
dd <- data.frame(rate = mortrate, moe = 1.96 * sqrt(mortrate * (1 -
mortrate))/10,
hosp = factor(paste('H', 1:100, sep = '')))
dim(dd)
[1] 100 3
# Set
XINLI LI gmail.com> writes:
>
> Dear R Users:
>
>I have the individual mortality rate and 95% CI of 100 hospitals,
> how to do the plot with the individual hospital in the Yaxis, and the
> mortality rate and 95% CI in the Xais and a overall mean as a reference
> line?
Something lik
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