YAS

.github/workflows/YASG.yml

@@ -11,6 +11,7 @@ on:
       - 'src/**'
       - 'test/**'
       - 'docs/**'
+      - 'ext/**'
       - '.github/workflows/YASG.yml'
       - 'format/**'
 jobs:

ext/EffectsGLMExt.jl

@@ -12,15 +12,15 @@ using StatsModels: TableRegressionModel
 _link(m::TableRegressionModel{<:AbstractGLM}) = Link(m.model)
 _link(m::AbstractGLM) = Link(m)
 
-function Effects._difference_method!(eff::Vector{T}, err::Vector{T}, 
-                                     model::Union{TableRegressionModel{<:AbstractGLM}, AbstractGLM}, 
-                                     ::AutoInvLink) where {T <: AbstractFloat}
+function Effects._difference_method!(eff::Vector{T}, err::Vector{T},
+                                     model::Union{TableRegressionModel{<:AbstractGLM},
+                                                  AbstractGLM},
+                                     ::AutoInvLink) where {T<:AbstractFloat}
     link = _link(model)
     err .*= mueta.(link, eff)
     eff .= linkinv.(link, eff)
 
     return err
 end
 
-
 end # module

ext/EffectsMixedModelsExt.jl

@@ -4,9 +4,9 @@ using Effects
 using MixedModels
 using GLM: Link, mueta, linkinv
 
-function Effects._difference_method!(eff::Vector{T}, err::Vector{T}, 
-                                     model::GeneralizedLinearMixedModel, 
-                                     ::AutoInvLink) where {T <: AbstractFloat}
+function Effects._difference_method!(eff::Vector{T}, err::Vector{T},
+                                     model::GeneralizedLinearMixedModel,
+                                     ::AutoInvLink) where {T<:AbstractFloat}
     link = Link(model)
     err .*= mueta.(link, eff)
     eff .= linkinv.(link, eff)

format/run.jl

@@ -3,7 +3,7 @@ using JuliaFormatter
 function main()
     perfect = true
     # note: keep in sync with `.github/workflows/format-check.yml`
-    for d in ["src/", "test/", "docs/"]
+    for d in ["src/", "ext/", "test/", "docs/"]
         @info "...linting $d ..."
         dir_perfect = format(d, YASStyle())
         perfect = perfect && dir_perfect

src/regressionmodel.jl

@@ -135,22 +135,21 @@ end
 # in addition to the difference method
 # xref https://github.com/JuliaStats/GLM.jl/blob/c13577eaf3f418c58020534dd407532ee57f219b/src/glmfit.jl#L773-L783
 
-function _difference_method!(eff::Vector{T}, err::Vector{T}, 
-                            ::RegressionModel, 
-                             invlink) where {T <: AbstractFloat}
-
+function _difference_method!(eff::Vector{T}, err::Vector{T},
+                             ::RegressionModel,
+                             invlink) where {T<:AbstractFloat}
     err .*= ForwardDiff.derivative.(invlink, eff)
     eff .= invlink.(eff)
     return eff, err
 end
 
-function _difference_method!(::Vector{T}, ::Vector{T}, 
-                             ::RegressionModel, 
-                             ::AutoInvLink) where {T <: AbstractFloat}
+function _difference_method!(::Vector{T}, ::Vector{T},
+                             ::RegressionModel,
+                             ::AutoInvLink) where {T<:AbstractFloat}
     @static if VERSION < v"1.9"
         @error "AutoInvLink requires extensions and is thus not available on Julia < 1.9."
     end
-    throw(ArgumentError("No appropriate extension is loaded for automatic " * 
+    throw(ArgumentError("No appropriate extension is loaded for automatic " *
                         "determination of the inverse link for this model type"))
 end
 

test/delta_method.jl

@@ -51,7 +51,7 @@ end
     dat[!, :vol] = dat.Volunteer .== "yes"
     model = glm(@formula(vol ~ Extraversion * Neuroticism), dat, Bernoulli())
     design = Dict(:Extraversion => [13],
-                 :Neuroticism => [16])
+                  :Neuroticism => [16])
     X = [1.0 13.0 16.0 13 * 16]
     iv = Base.Fix1(GLM.linkinv, Link(model.model))
     @static if VERSION >= v"1.9"
@@ -65,18 +65,18 @@ end
 
             # compare with results from GLM.predict
             pred = DataFrame(predict(model.model, X;
-                                    interval=:confidence,
-                                    interval_method=:delta,
-                                    level))
+                                     interval=:confidence,
+                                     interval_method=:delta,
+                                     level))
             @test all(pred.prediction .≈ eff.vol)
             @test all(isapprox.(pred.lower, eff.lower; atol=0.001))
             @test all(isapprox.(pred.upper, eff.upper; atol=0.001))
 
             eff_trans = effects(design, model; level)
             transform!(eff_trans,
-                    :vol => ByRow(iv),
-                    :lower => ByRow(iv),
-                    :upper => ByRow(iv); renamecols=false)
+                       :vol => ByRow(iv),
+                       :lower => ByRow(iv),
+                       :upper => ByRow(iv); renamecols=false)
             # for this model, things play out nicely
             @test all(eff_trans.vol .≈ eff.vol)
             @test all(isapprox.(eff_trans.lower, eff.lower; atol=0.001))
@@ -92,7 +92,8 @@ end
         @test isapprox(only(eff_emm.upper), -0.292; atol=0.005)
 
         # emmeans(model, ~ neuroticism * extraversion, level=0.68, transform="response")
-        eff_emm_trans = effects(Dict(:Extraversion => [12.4], :Neuroticism => [11.5]), model;
+        eff_emm_trans = effects(Dict(:Extraversion => [12.4], :Neuroticism => [11.5]),
+                                model;
                                 invlink)
         @test isapprox(only(eff_emm_trans.vol), 0.414; atol=0.005)
         @test isapprox(only(eff_emm_trans.err), 0.0133; atol=0.005)
@@ -103,13 +104,13 @@ end
 
 @static if VERSION >= v"1.9"
     @testset "link function in a MixedModel" begin
-        model = fit(MixedModel, 
-                    @formula(use ~ 1 + age + (1|urban)), 
-                    MixedModels.dataset(:contra), 
+        model = fit(MixedModel,
+                    @formula(use ~ 1 + age + (1 | urban)),
+                    MixedModels.dataset(:contra),
                     Bernoulli(); progress=false)
         design = Dict(:age => -10:10)
-        eff_manual = effects(design, model; 
-                            invlink=Base.Fix1(GLM.linkinv, Link(model)))
+        eff_manual = effects(design, model;
+                             invlink=Base.Fix1(GLM.linkinv, Link(model)))
         eff_auto = effects(design, model; invlink=AutoInvLink())
 
         @test all(isapprox.(Matrix(eff_manual), Matrix(eff_auto)))