ForestPlot

Documentation for ForestPlot.

ForestPlot is a simple package to draw forest plots for mata-analysis study.

Examples

using ForestPlot, Plots

p = 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)

png(p, "plot1.png")

"plot1.png"

p = 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))

png(p, "plot2.png")

"plot2.png"

p = 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],
    summary= Dict(:ci => [0.75,1.15], :est => 0.9),
    logscale = true, title = "Title")

png(p, "plot3.png")

"plot3.png"

p = 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"],
    cimszwts = [1.0, 2.0, 3.0, 2.5, 4.0, 4.0, 0.5],
    sourcelabel = "Study:", metriclabel = "Estimate",
    summary= Dict(:ci => [0.75,1.15], :est => 0.9),
    logscale = false, title = ["" "Title"], size = (800, 400))

png(p, "plot4.png")

"plot4.png"

ForestPlot.forestplot

ForestPlot.forestplot — Method

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), 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 (if nothing - 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))

source