### copy data into 'dat' and examine data
dat <- dat.hart1999
dat
if (FALSE) {
### load metafor package
library(metafor)
### calculate log incidence rate ratios and corresponding sampling variances
dat <- escalc(measure="IRR", x1i=x1i, x2i=x2i, t1i=t1i, t2i=t2i, data=dat)
dat
### meta-analysis of log incidence rate ratios using a random-effects model
res <- rma(yi, vi, data=dat)
res
### average incidence rate ratio with 95% CI
predict(res, transf=exp)
### forest plot with extra annotations
par(mar=c(5,4,1,2))
forest(res, xlim=c(-11, 5), at=log(c(0.05, 0.25, 1, 4)), atransf=exp,
slab=paste0(study, " (", year, ")"),
ilab=cbind(paste(x1i, "/", t1i, sep=" "),
paste(x2i, "/", t2i, sep=" ")),
ilab.xpos=c(-6.5,-4), cex=0.85, header="Study (Year)")
op <- par(cex=0.85, font=2)
text(c(-6.5,-4), 8.5, c("Warfarin", "Control"))
text(c(-6.5,-4), 7.5, c("Strokes / PT", "Strokes / PT"))
segments(x0=-8, y0=8, x1=-2.75, y1=8)
par(op)
### meta-analysis of incidence rate differences using a random-effects model
res <- rma(measure="IRD", x1i=x1i, x2i=x2i, t1i=t1i, t2i=t2i, data=dat)
res
}
Run the code above in your browser using DataLab