ForestPlot.forestplot
— Methodforestplot(ci; sourcelabel = "Source:", metriclabel = "OR", cilabel = "CI95%",
source = nothing, metric = nothing, printci = false,
summary = nothing, logscale = true, cimsz = -1, cimszwts = nothing, size = (600, 400), ticksn = 5, 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 (ifnothing
-metric
will be used);size
- size of plot;ticksn
- number of ticks;- metriclabel = "OR" - label for metrics values;
- cilabel = "CI95%"- label for intervals values
- ps = 10 - font size in points;
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 (true/false or vlues for vertical lines)
- :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))