plot.netposet

0th

Percentile

Scatter plot of partially order of treatment ranks

This function generates a scatter plot of a partial order of treatment ranks.

Keywords
hplot, poset, Scatterplot of partially ordered rankings
Usage
# S3 method for netposet
plot(x,
     pooled=ifelse(x$comb.random, "random", "fixed"),
     sel.x = 1, sel.y = 2, sel.z = 3,
     dim = "2d",
     cex = 1, col = "black",
     adj.x = 0, adj.y = 1,
     offset.x = 0.005, offset.y = -0.005,
     arrows = FALSE,
     col.lines = "black", lty.lines = 1, lwd.lines = 1,
     length = 0.05,
     grid = TRUE,
     col.grid = "gray", lty.grid = 2, lwd.grid = 1,
     ...)
Arguments
x

An object of class netmeta (mandatory).

pooled

A character string indicating whether scatter plot should be drawn for fixed effect ("fixed") or random effects model ("random"). Can be abbreviated.

sel.x

.

sel.y

.

sel.z

.

dim

A character string indicating whether a 2- or 3-dimensional plot should be produced, either "2d" or "3d".

cex

The magnification to be used for treatment labels.

col

A vector with with colour of treatment labels.

adj.x

Value(s) in [0, 1] to specify adjustment of treatment labels on x-axis; see text.

adj.y

Value(s) in [0, 1] to specify adjustment of treatment labels on y-axis; see text.

offset.x

Offset of treatment labels on x-axis.

offset.y

Offset of treatment labels on x-axis.

arrows

A logical indicating whether arrows should be printed.

col.lines

Line colour.

lty.lines

Line type.

lwd.lines

Line width.

length

Length of arrows; see arrows.

grid

A logical indicating whether a grid lines should be added to plot.

col.grid

Colour of grid lines.

lty.grid

Line type of grid lines.

lwd.grid

Line width of grid lines.

Additional graphical arguments.

Details

Scatter plot ...

In order to generate 3-D plots (argument dim = "3d"), R package rgl is necessary. Note, under macOS the X.Org X Window System must be available (see https://www.xquartz.org).

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, hasse

Aliases
  • plot.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)
#
# Scatter plot
#
plot(po)
# }
Documentation reproduced from package netmeta, version 0.9-5, License: GPL (>= 2)

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