# NOT RUN {
### copy data into 'dat' and examine data
dat <- dat.hackshaw1998
dat
### random-effects model using the log odds ratios
res <- rma(yi, vi, data=dat, method="DL")
res
### estimated average odds ratio with CI (and prediction interval)
predict(res, transf=exp, digits=2)
### illustrate how the log odds ratios and corresponding sampling variances
### were back-calculated based on the reported odds ratios and CI bounds
dat$yi <- log(dat$or)
dat$vi <- ((log(dat$or.ub) - log(dat$or.lb)) / (2*qnorm(.975)))^2
# }
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