install.packages("meta")

library(meta)

data("Olkin95") # 70 studies

m1 <- metabin(event.e, n.e, event.c, n.c, data=Olkin95)
m1

# Subgroup analysis (subgroups defined by dividing studies in two parts a 35 studies)
m2 <- update(m1, byvar = m1$studlab <= 35)
# One large forest plot, only with a slightly greater gap between the subgroups
# (for cutting it up using graphic tools outside R)
pdf("LargeForest.pdf", height = 16)
forest(m2, print.byvar = FALSE, print.subgroup.labels = FALSE, 
       comb.fixed = FALSE, comb.random = FALSE, hetstat = FALSE)
dev.off()

# Separate analyses by subsets 
m3 <- update(m1, subset = m1$studlab <= 35)
forest(m3, comb.fixed = FALSE, comb.random = FALSE, hetstat = FALSE)
m4 <- update(m1, subset = m1$studlab > 35)
forest(m4, comb.fixed = FALSE, comb.random = FALSE, hetstat = FALSE)
# Limitations: 
# 1. No pooled estimate for all studies together
# 2. Weights refer only to subsets, therefore not comparable between subsets
# Alternatively, make all markers equally large:
forest(m3, comb.fixed = FALSE, comb.random = FALSE, hetstat = FALSE, weight.study = "same")
forest(m4, comb.fixed = FALSE, comb.random = FALSE, hetstat = FALSE, weight.study = "same")