How to fix an error related to the Effects package

I want to run the average marginal effects between two predictors: education and unemployment rate. While the package Effects in Julia can do the trick, i am having an error which i will describe below. First, i show the code that works perfectly fine and the results i get from running the MixedModels package. Second, i show the part of the code that is not working.

dffnm = "df4_full"
df = DataFrame(Arrow.Table(dffnm))

df1 = DataFrame( 
    unemploy = disallowmissing(df.macro_unemployment),
    workhours_imputed = df.workhours_imputed,
    education = PooledArray(,
    id = PooledArray(string.(disallowmissing(,
    age = Int8.(disallowmissing(df.age)) .- Int8(42), # center the age at 42
    sex = PooledArray(,)

form1 = @formula workhours_imputed ~ 1 + sex + age  + education + education * unemploy + sex * unemploy + (1|id)

contr = Dict(nm => Grouping() for nm in (:country, :country_year, :id))

contr = Dict(:country => Grouping(),
             :country_year => Grouping(),
             :id => Grouping(),
             :sex => DummyCoding(base="Female"),
             :education => DummyCoding(base="Tertiary"))

m1 = @time fit(MixedModel, form1, df1, contrasts=contr)

Here is the output:
Screenshot 2021-11-10 at 17.10.59

Everything works perfectly so far. The aim is to run the average marginal effects for education and unemployment on working hours. However, i thought that i would start with a simpler example which is just taking the average marginal effects of education (i follow their example here: Home · Effects.jl):

design = Dict(:education => unique(df1))

Dict{Symbol, Vector{Union{Missing, String}}} with 1 entry:
  :education => ["Tertiary", "Upper-secondary", "Below upper-secondary", missin…

Then the last line of code:

effects(design, m1)

KeyError: key missing not found

  [1] getindex(h::Dict{String, Int64}, key::Missing)
    @ Base ./dict.jl:482
  [2] _broadcast_getindex_evalf
    @ ./broadcast.jl:648 [inlined]

Could someone help me to fix this? I am also unsure how to run the average marginal effects for the interaction between education and unemployment rate.

Can you drop the missing from that vector and see if that works?

Thanks for the suggestion, it worked great.