EffectSizes.jl

EffectSizes.jl is a Julia package for effect size measures. Confidence intervals are assigned to effect sizes using the Normal distribution or by bootstrap resampling.

The package implements types for the following measures:

Measure	Type
Cohen's d	CohenD
Hedge's g	HedgeG
Glass's Δ	GlassΔ

Installation

julia> import Pkg; Pkg.add("EffectSizes");

Examples

julia> using Random, EffectSizes; Random.seed!(1);

julia> xs = randn(10^3);

julia> ys = randn(10^3) .+ 0.5;

julia> es = CohenD(xs, ys, quantile=0.95); # normal CI (idealised distribution)

julia> typeof(es)
CohenD{Float64, ConfidenceInterval{Float64}}

julia> effectsize(es)
-0.5035709742336323

julia> quantile(es)
0.95

julia> ci = confint(es);

julia> typeof(ci)
ConfidenceInterval{Float64}

julia> confint(ci)
(-0.5926015897640895, -0.41454035870317507)

julia> es = CohenD(xs, ys, 10^4, quantile=0.95); # bootstrap CI (empirical distribution)

julia> effectsize(es) # effect size is the same
-0.5035709742336323

julia> typeof(es)
CohenD{Float64, BootstrapConfidenceInterval{Float64}}

julia> ci = confint(es); # confidence interval is different

julia> lower(ci)
-0.5919535584593746

julia> upper(ci)
-0.4155997394380884

Contributing

Ideas and PRs are very welcome.