lrtest fails on doc string example / for GLM Models

[awadell1]

Per the doc strings for lrtest:

julia> using DataFrames, GLM
  
julia> dat = DataFrame(Result=[1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1],
                       Treatment=[1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2],
                       Other=categorical([1, 1, 2, 1, 2, 1, 3, 1, 1, 2, 2, 1]));

julia> nullmodel = glm(@formula(Result ~ 1), dat, Binomial(), LogitLink());

julia> model = glm(@formula(Result ~ 1 + Treatment), dat, Binomial(), LogitLink());

julia> bigmodel = glm(@formula(Result ~ 1 + Treatment + Other), dat, Binomial(), LogitLink());

julia> lrtest(nullmodel, model, bigmodel)
Likelihood-ratio test: 3 models fitted on 12 observations
──────────────────────────────────────────────
     DOF  ΔDOF  Deviance  ΔDeviance  p(>Chisq)
──────────────────────────────────────────────
[1]    1         16.3006
[2]    2     1   15.9559    -0.3447     0.5571
[3]    4     2   14.0571    -1.8988     0.3870
──────────────────────────────────────────────

julia> lrtest(bigmodel, model, nullmodel)
Likelihood-ratio test: 3 models fitted on 12 observations
──────────────────────────────────────────────
     DOF  ΔDOF  Deviance  ΔDeviance  p(>Chisq)
──────────────────────────────────────────────
[1]    4         14.0571
[2]    2    -2   15.9559     1.8988     0.3870
[3]    1    -1   16.3006     0.3447     0.5571
──────────────────────────────────────────────

However, categorical is not defined (Shows up in doctests too: https://github.com/JuliaStats/StatsModels.jl/runs/4027286993?check_suite_focus=true#step:4:2433). Adding a using CategoricalArrays also errors with:

julia> using DataFrames, GLM, CategoricalArrays

julia> dat = DataFrame(Result=[1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1],
                                     Treatment=[1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2],
                                     Other=categorical([1, 1, 2, 1, 2, 1, 3, 1, 1, 2, 2, 1]));

julia> nullmodel = glm(@formula(Result ~ 1), dat, Binomial(), LogitLink());

julia> model = glm(@formula(Result ~ 1 + Treatment), dat, Binomial(), LogitLink());

julia> bigmodel = glm(@formula(Result ~ 1 + Treatment + Other), dat, Binomial(), LogitLink());

julia> lrtest(nullmodel, model, bigmodel)
ERROR: MethodError: no method matching isnested(::GeneralizedLinearModel{GLM.GlmResp{Vector{Float64}, Binomial{Float64}, LogitLink}, GLM.DensePredChol{Float64, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}}}, ::GeneralizedLinearModel{GLM.GlmResp{Vector{Float64}, Binomial{Float64}, LogitLink}, GLM.DensePredChol{Float64, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}}}; atol=0.0)
Stacktrace:
 [1] isnested(m1::StatsModels.TableRegressionModel{GeneralizedLinearModel{GLM.GlmResp{Vector{Float64}, Binomial{Float64}, LogitLink}, GLM.DensePredChol{Float64, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}}}, Matrix{Float64}}, m2::StatsModels.TableRegressionModel{GeneralizedLinearModel{GLM.GlmResp{Vector{Float64}, Binomial{Float64}, LogitLink}, GLM.DensePredChol{Float64, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}}}, Matrix{Float64}}; kwargs::Base.Iterators.Pairs{Symbol, Float64, Tuple{Symbol}, NamedTuple{(:atol,), Tuple{Float64}}})
   @ StatsModels ~/.julia/packages/StatsModels/m1jYD/src/statsmodel.jl:147
 [2] lrtest(::StatsModels.TableRegressionModel{GeneralizedLinearModel{GLM.GlmResp{Vector{Float64}, Binomial{Float64}, LogitLink}, GLM.DensePredChol{Float64, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}}}, Matrix{Float64}}, ::Vararg{StatsModels.TableRegressionModel{GeneralizedLinearModel{GLM.GlmResp{Vector{Float64}, Binomial{Float64}, LogitLink}, GLM.DensePredChol{Float64, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}}}, Matrix{Float64}}, N} where N; atol::Float64)
   @ StatsModels ~/.julia/packages/StatsModels/m1jYD/src/lrtest.jl:90
 [3] lrtest(::StatsModels.TableRegressionModel{GeneralizedLinearModel{GLM.GlmResp{Vector{Float64}, Binomial{Float64}, LogitLink}, GLM.DensePredChol{Float64, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}}}, Matrix{Float64}}, ::Vararg{StatsModels.TableRegressionModel{GeneralizedLinearModel{GLM.GlmResp{Vector{Float64}, Binomial{Float64}, LogitLink}, GLM.DensePredChol{Float64, LinearAlgebra.Cholesky{Float64, Matrix{Float64}}}}, Matrix{Float64}}, N} where N)
   @ StatsModels ~/.julia/packages/StatsModels/m1jYD/src/lrtest.jl:74
 [4] top-level scope
   @ REPL[84]:1

[jerlich]

dat = DataFrame(Result=[1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 1, 1],
                       Treatment=[1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2],
                       Other=string.([1, 1, 2, 1, 2, 1, 3, 1, 1, 2, 2, 1]));

works.