# NOT RUN {
data(Linde2015)
# Define order of treatments
#
trts <- c("TCA", "SSRI", "SNRI", "NRI",
"Low-dose SARI", "NaSSa", "rMAO-A", "Hypericum",
"Placebo")
#
# Outcome labels
#
outcomes <- c("Early response", "Early remission")
# (1) Early response
#
p1 <- pairwise(treat = list(treatment1, treatment2, treatment3),
event = list(resp1, resp2, resp3),
n = list(n1, n2, n3),
studlab = id, data = Linde2015, sm = "OR")
#
net1 <- netmeta(p1, comb.fixed = FALSE,
seq = trts, ref = "Placebo")
# (2) Early remission
#
p2 <- pairwise(treat = list(treatment1, treatment2, treatment3),
event = list(remi1, remi2, remi3),
n = list(n1, n2, n3),
studlab = id, data = Linde2015, sm = "OR")
#
net2 <- netmeta(p2, comb.fixed = FALSE,
seq = trts, ref = "Placebo")
# Partial order of treatment rankings
#
po2 <- netposet(netrank(net1, small.values = "bad"),
netrank(net2, small.values = "bad"),
outcomes = outcomes)
# Scatter plot
#
plot(po2)
# Same scatter plot as only two outcomes considered in netposet()
#
plot(po2, "biplot")
# Consider three outcomes
#
# Outcome labels
#
outcomes <- c("Early response", "Early remission", "Lost to follow-up")
# (3) Loss to follow-up
#
p3 <- pairwise(treat = list(treatment1, treatment2, treatment3),
event = list(loss1, loss2, loss3),
n = list(n1, n2, n3),
studlab = id, data = Linde2015, sm = "OR")
#
net3 <- netmeta(p3, comb.fixed = FALSE,
seq = trts, ref = "Placebo")
# Partial order of treatment rankings (with three outcomes)
#
po3 <- netposet(netrank(net1, small.values = "bad"),
netrank(net2, small.values = "bad"),
netrank(net3, small.values = "good"),
outcomes = outcomes)
# Hasse diagram
#
hasse(po3)
# Scatter plot
#
plot(po3)
# Biplot (reverse limits of y-axis as biplot is upside down)
#
plot(po3, "bi", xlim = c(-1, 1.7), ylim = c(2.5, -2.5))
# }
# NOT RUN {
# }
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