Hasse diagram
This function generates a Hasse diagram for a partial order of treatment ranks in a network meta-analysis.
hasse(x, pooled = ifelse(x$comb.random, "random", "fixed"), newpage = TRUE)
x |
An object of class |
pooled |
A character string indicating whether Hasse diagram
show be drawn for fixed effect ( |
newpage |
A logical value indicating whether a new figure should be printed in an existing graphics window. Otherwise, the Hasse diagram is added to the existing figure. |
Generate a Hasse diagram (Carlsen & Bruggemann, 2014) for a partial order of treatment ranks in a network meta-analysis (Rücker & Schwarzer, 2017).
This R function is a wrapper function for R function
hasse in R package hasseDiagram
(Krzysztof Ciomek, https://github.com/kciomek/hasseDiagram),
i.e., function hasse can only be used if R package
hasseDiagram is installed.
Gerta Rücker ruecker@imbi.uni-freiburg.de, Guido Schwarzer sc@imbi.uni-freiburg.de
Carlsen L, Bruggemann R (2014): Partial order methodology: a valuable tool in chemometrics. Journal of Chemometrics, 28, 226–34
Rücker G, Schwarzer G (2017): Resolve conflicting rankings of outcomes in network meta-analysis: Partial ordering of treatments. Research Synthesis Methods, 8, 526–36
## Not run:
# Use depression dataset
#
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", small.values = "bad")
# (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", small.values = "bad")
# Partial order of treatment rankings
#
po <- netposet(netrank(net1), netrank(net2), outcomes = outcomes)
# Hasse diagram
#
hasse(po)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.