ERROR: MethodError: Cannot convert an object of type Tuple{Matrix{Float64}, ReMat{Float64, 1}} to an object of type Matrix{Float64}

[ParadaCarleton]

using Tables
using MixedModels
using CSVFiles

const GLMM = GeneralizedLinearMixedModel

data = load("ICARdata.csv") |> Tables.rows
regression = @formula(SEI ~ Age + Total + Sex + (1 | Education))
model = fit(GLMM, regression, data, Normal, LogitLink)

Results in:

ERROR: MethodError: Cannot `convert` an object of type Tuple{Matrix{Float64}, ReMat{Float64, 1}} to an object of type Matrix{Float64}

Closest candidates are:
  convert(::Type{Array{S, N}}, ::PooledArrays.PooledArray{T, R, N}) where {S, T, R, N}
   @ PooledArrays ~/.julia/packages/PooledArrays/DXlaI/src/PooledArrays.jl:499
  convert(::Type{Array{T, N}}, ::StaticArraysCore.SizedArray{S, T, N, N, Array{T, N}}) where {S, T, N}
   @ StaticArrays ~/.julia/packages/StaticArrays/80e5O/src/SizedArray.jl:88
  convert(::Type{Array{T, N}}, ::StaticArraysCore.SizedArray{S, T, N, M, TData} where {M, TData<:AbstractArray{T, M}}) where {T, S, N}
   @ StaticArrays ~/.julia/packages/StaticArrays/80e5O/src/SizedArray.jl:82
  ...

Stacktrace:
 [1] StatsModels.ModelMatrix{Matrix{Float64}}(mf::StatsModels.ModelFrame{NamedTuple{(:SEI, :Age, :Total, :Sex, :Education), Tuple{Vector{Int64}, Vector{Float64}, …}}, GeneralizedLinearMixedModel})
   @ StatsModels ~/.julia/packages/StatsModels/Wzvuu/src/modelframe.jl:226
 [2] StatsModels.ModelMatrix(mf::StatsModels.ModelFrame{NamedTuple{(:SEI, :Age, :Total, :Sex, :Education), Tuple{Vector{Int64}, Vector{Float64}, …}}, GeneralizedLinearMixedModel})
   @ StatsModels ~/.julia/packages/StatsModels/Wzvuu/src/modelframe.jl:229
 [3] fit(::Type{GeneralizedLinearMixedModel}, ::StatsModels.FormulaTerm{StatsModels.Term, Tuple{StatsModels.Term, StatsModels.FunctionTerm{typeof(^), Vector{StatsModels.AbstractTerm}}, …}}, ::Tables.IteratorWrapper{TableTraitsUtils.TableIterator{NamedTuple{(Symbol(""), :Age, :Sex, :Education, :SEI, Symbol("MR.45"), Symbol("MR.46"), Symbol("MR.47"), Symbol("MR.55"), Symbol("LN.07"), Symbol("LN.33"), Symbol("LN.34"), Symbol("LN.58"), Symbol("VR.04"), Symbol("VR.16"), Symbol("VR.17"), Symbol("VR.19"), Symbol("R3D.03"), Symbol("R3D.04"), Symbol("R3D.06"), Symbol("R3D.08"), :Total), Tuple{Int64, Float64, …}}, Tuple{Vector{Int64}, Vector{Float64}, …}}}, ::Type, ::Vararg{Type}; contrasts::Dict{Symbol, Any}, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
   @ StatsModels ~/.julia/packages/StatsModels/Wzvuu/src/statsmodel.jl:86
 [4] fit(::Type{GeneralizedLinearMixedModel}, ::StatsModels.FormulaTerm{StatsModels.Term, Tuple{StatsModels.Term, StatsModels.FunctionTerm{typeof(^), Vector{StatsModels.AbstractTerm}}, …}}, ::Tables.IteratorWrapper{TableTraitsUtils.TableIterator{NamedTuple{(Symbol(""), :Age, :Sex, :Education, :SEI, Symbol("MR.45"), Symbol("MR.46"), Symbol("MR.47"), Symbol("MR.55"), Symbol("LN.07"), Symbol("LN.33"), Symbol("LN.34"), Symbol("LN.58"), Symbol("VR.04"), Symbol("VR.16"), Symbol("VR.17"), Symbol("VR.19"), Symbol("R3D.03"), Symbol("R3D.04"), Symbol("R3D.06"), Symbol("R3D.08"), :Total), Tuple{Int64, Float64, …}}, Tuple{Vector{Int64}, Vector{Float64}, …}}}, ::Type, ::Type)
   @ StatsModels ~/.julia/packages/StatsModels/Wzvuu/src/statsmodel.jl:78
 [5] top-level scope
   @ REPL[29]:1

[palday]

What happens if you do

model = fit(GLMM, regression, data, Normal(), LogitLink())

? In other words, you need to pass instances, not types.

[ParadaCarleton]

What happens if you do

model = fit(GLMM, regression, data, Normal(), LogitLink())

? In other words, you need to pass instances, not types.

Works then, thanks! Yeah, this seems to be a problem with error messages.