YAS

ext/EffectsMixedModelsExt.jl

@@ -41,7 +41,8 @@ Use the results of a bootstrap to compute empirical error estimates
     This method is experimental and may change in its defaults or
     disappear entirely in a future release!
 """
-function Effects.effects!(reference_grid::DataFrame, model::MixedModel, boot::MixedModelBootstrap;
+function Effects.effects!(reference_grid::DataFrame, model::MixedModel,
+                          boot::MixedModelBootstrap;
                           eff_col=nothing, err_col=:err, typical=mean, invlink=identity,
                           lower_col=:lower, upper_col=:upper,
                           level=nothing)
@@ -66,7 +67,6 @@ function Effects.effects!(reference_grid::DataFrame, model::MixedModel, boot::Mi
     reference_grid[!, something(eff_col, _responsename(model))] = eff
     reference_grid[!, err_col] = err
 
-
     # logic here is slightly different than for other methods
     # because we can compute empirical CIs instead of relying on a Wald
     # approximation
@@ -98,13 +98,14 @@ Use the results of a bootstrap to compute empirical error estimates
     disappear entirely in a future release!
 """
 function Effects.effects(design::AbstractDict, model::MixedModel, boot::MixedModelBootstrap;
-                 eff_col=nothing, err_col=:err, typical=mean,
-                 lower_col=:lower, upper_col=:upper, invlink=identity,
-                 level=nothing)
+                         eff_col=nothing, err_col=:err, typical=mean,
+                         lower_col=:lower, upper_col=:upper, invlink=identity,
+                         level=nothing)
     grid = expand_grid(design)
     dv = something(eff_col, _responsename(model))
     level = isnothing(level) ? 0.68 : level
-    effects!(grid, model, boot; eff_col=dv, err_col, typical, invlink, level, lower_col, upper_col)
+    effects!(grid, model, boot; eff_col=dv, err_col, typical, invlink, level, lower_col,
+             upper_col)
     return grid
 end
 

test/mixedmodels.jl

@@ -26,7 +26,7 @@ eff = effects(design, model)
 @test eff.y + eff.err ≈ eff.upper
 
 β = fixef(model)
-@test only(eff.y) ≈ β[1] + 2 * β[2]  + β[3]
+@test only(eff.y) ≈ β[1] + 2 * β[2] + β[3]
 
 # there is one bit of weirdness -- the removed coefficients behave like any other
 # variable in the "design" that is missing from the model.
@@ -50,9 +50,9 @@ bootdf = unstack(DataFrame(boot.β), :coefname, :β)
 # now make sure the bootstrap gives approximately the same results
 eff_boot = effects(design, model, boot)
 @test eff_boot.y ≈ eff.y
-@test eff_boot.err ≈ eff.err atol=0.005
+@test eff_boot.err ≈ eff.err atol = 0.005
 
 eff95 = effects(design, model; level=0.95)
 eff_boot95 = effects(design, model, boot; level=0.95)
-@test eff_boot95.lower ≈ eff95.lower atol=0.1
-@test eff_boot95.upper ≈ eff95.upper atol=0.1
+@test eff_boot95.lower ≈ eff95.lower atol = 0.1
+@test eff_boot95.upper ≈ eff95.upper atol = 0.1