netmeta (version 0.9-6)

hasse: Hasse diagram

Description

This function generates a Hasse diagram for a partial order of treatment ranks in a network meta-analysis.

Usage

hasse(x,
      pooled=ifelse(x$comb.random, "random", "fixed"),
      newpage = TRUE)

Arguments

x

An object of class netposet (mandatory).

pooled

A character string indicating whether Hasse diagram show be drawn for fixed effect ("fixed") or random effects model ("random"). Can be abbreviated.

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.

Details

Generate a Hasse diagram for a partial order of treatment ranks in a network meta-analysis (Carlsen and Bruggemann, 2014).

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.

References

Carlsen L, Bruggemann R (2014), Partial order methodology: a valuable tool in chemometrics. Journal of Chemometrics, 28 226--34, DOI:10.1002/cem.2569

See Also

netmeta, netposet

Examples

# 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, comb.random = TRUE,
                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, comb.random = TRUE,
                seq = trts, ref = "Placebo")
#
# Partial order of treatment rankings (all five outcomes)
#
po <- netposet(netrank(net1, small.values = "bad"),
               netrank(net2, small.values = "bad"),
               outcomes = outcomes)
#
# Hasse diagram
#
hasse(po)
# }