How to create odds ratio and 95 % CI plot in R - r

Question

I have estimates of odds ratio with corresponding 95% CI of six pollutants overs 4 lag periods. How can I create a vertical plot similar to the attached figure in R? The figure below was created in SPSS.
Sample data that produced the figure is the following:
lag pollut or lcl ucl
0 CO 0.97 0.90 1.06
0 PM10 1.00 0.91 1.09
0 NO 0.97 0.92 1.02
0 NO2 1.01 0.89 1.15
0 SO2 0.97 0.85 1.11
0 Ozone 1.00 0.87 1.15
1 CO 1.03 0.95 1.10
1 PM10 0.93 0.86 1.01
1 NO 1.01 0.97 1.06
1 NO2 1.08 0.97 1.20
1 SO2 0.94 0.84 1.04
1 Ozone 0.94 0.84 1.04
2 CO 1.09 1.02 1.16
2 PM10 1.04 0.96 1.13
2 NO 1.04 1.00 1.08
2 NO2 1.07 0.96 1.18
2 SO2 1.05 0.95 1.17
2 Ozone 0.93 0.84 1.03
3 CO 0.98 0.91 1.06
3 PM10 1.14 1.05 1.24
3 NO 0.99 0.95 1.04
3 NO2 1.01 0.91 1.12
3 SO2 1.11 1.00 1.23
3 Ozone 1.00 0.90 1.11

Answer 1

You can also do this with ggplot2. The code is somewhat shorter:
dat <- read.table("clipboard", header = T)
dat$lag <- paste0("L", dat$lag)
library(ggplot2)
ggplot(dat, aes(x = pollut, y = or, ymin = lcl, ymax = ucl)) + geom_pointrange(aes(col = factor(lag)), position=position_dodge(width=0.30)) +
ylab("Odds ratio & 95% CI") + geom_hline(aes(yintercept = 1)) + scale_color_discrete(name = "Lag") + xlab("")
EDIT: Here is a version is closer to the SPSS figure:
ggplot(dat, aes(x = pollut, y = or, ymin = lcl, ymax = ucl)) + geom_linerange(aes(col = factor(lag)), position=position_dodge(width=0.30)) +
geom_point(aes(shape = factor(lag)), position=position_dodge(width=0.30)) + ylab("Odds ratio & 95% CI") + geom_hline(aes(yintercept = 1)) + xlab("")

Answer 2

Assuming your data are in datf...
I'd sort it first into just what you want order wise.
datf <- datf[order(datf$pollut, datf$lag), ]
You want a space before and after every lab grouping so I'd add some extra rows in that are NA. That makes it easier because then you'll automatically have blanks in your plot calls.
datfPlusNA <- lapply(split(datf, datf$pollut), function(x) rbind(NA, x, NA))
datf <- do.call(rbind, datfPlusNA)
Now that you have your data.frame sorted and with the extra NAs the plotting is easy.
nr <- nrow(datf) # find out how many rows all together
with(datf, {# this allows entering your commands more succinctly
# first you could set up the plot so you can select the order of drawing
plot(1:nr, or, ylim = c(0.8, 1.3), type = 'n', xaxt = 'n', xlab = '', ylab = 'Odds Ratio and 95% CI', frame.plot = TRUE, panel.first = grid(nx = NA, ny = NULL))
# arrows(1:nr, lcl, 1:nr, ucl, length = 0.02, angle = 90, code = 3, col = factor(lag))
# you could use arrows above but you don't want ends so segments is easier
segments(1:nr, lcl, 1:nr, ucl, col = factor(lag))
# add your points
points(1:nr, or, pch = 19, cex = 0.6)
xLabels <- na.omit(unique(pollut))
axis(1, seq(4, 34, by = 6) - 0.5, xLabels)
})
abline(h = 1.0)
There are packages that make this kind of thing easier but if you can do it like this you can start doing any graphs that you can imagine.