ForestPlot.forestplotMethod
forestplot(ci; sourcelabel = "Source:", metriclabel = "OR", cilabel = "CI95%", 
source = nothing, metric = nothing, printci = false,
summary = nothing, logscale = true, cimsz = -1, cimszwts = nothing, size = (600, 400), kwargs...)

By default plot is logscaled.

  • ci - vector (iterable) of confidence intervals bounds;
  • source - vector of study names (String);
  • metric - vector of metric estimates;
  • printci - print confidence interval;
  • summary - print summary object (Dict);
  • logscale - if true CI will be transformed (exp function used);
  • cimsz - CI marker size, -1 or any value < 0 - auto;
  • cimszwts - CI marker size weights (if nothing - metric will be used);
  • size - size of plot.

Example

using ForestPlot

forestplot([[0.2,1.2], [0.8,1.4], [0.6, 0.8], [1.2, 1.6]], 
sourcelabel = "Study:", metriclabel = "Estimate",
metric = [1.0, 1.2, 0.7, 1.3], 
source = ["12345678901234567890", "B", "C", "D"])

Summary object

Summary is a Dict() with keywords:

  • :ci
  • :est
  • :vline
  • :markershape
  • :markersize

Example 1

forestplot([[0.2,1.2], [0.8,1.4], [0.6, 0.8], [1.2, 1.6]], 
metric = [1.0, 1.2, 0.7, 1.3], source = ["A", "B", "C", "D"],
summary = Dict(:ci =>[0.8, 1.1], :est => 0.95, :markershape => :rtriangle), logscale = false)

Example 2

forestplot([[0.2,1.2], [0.8,1.4], [0.6, 0.8], [1.2, 1.6], [0.3, 0.7], [1.2, 1.5], [1.2, 1.3]], 
metric = [1.0, 1.2, 0.7, 1.3, 0.5, 1.2, 1.3], source = ["A", "B", "C", "D", "E", "F", "G"],
sourcelabel = "Study:", metriclabel = "Estimate", 
summary= Dict(:ci => [0.75,1.15], :est => 0.9), 
logscale = true, printci = true, title = ["" "Title"], size = (800, 400))