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See line 22-27 in by.jl
for i = 1:nd
filtered_dx = filter(!isnan, Xt_mat[i, :] .- X.statistic[i])
push!(ses, sqrt(sum(filtered_dx .^ 2) / length(filtered_dx)))
end
replace!(ses, NaN => 0)
X.SE = sesThis is hardcoding the variance for "bootstrap" type ReplicateDesign. For future additions, like JKn, the variance is calculated differently.
TODO: Update bydomain function with modularity for current and future methods of variance estimation.
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