## load package
library("margins")
library(fabricatr)
library(randomizr)
library(miceadds)

## code goes here
set.seed(42)
dat <- fabricate(
        N = 100,                        # sample size
        x = runif(N, 0, 1),             # pre-treatment covariate
        y0 = rnorm(N, mean = x),        # control potential outcome
        y1 = y0 + 0.35,                 # treatment potential outcome
        z = complete_ra(N),             # complete random assignment to treatment
        y = ifelse(z, y1, y0),          # observed outcome
        
        # We will also consider clustered data
        clust = sample(rep(letters[1:20], each = 5)),
        z_clust = cluster_ra(clust),
        y_clust = ifelse(z_clust, y1, y0)
)

lmout_cl <- lm.cluster(y_clust ~ z_clust + x, data=dat, cluster="clust")
mar_cl <- with(lmout_cl, margins(lm_res, vcov=vcov))

## session info for your system
sessionInfo()
R version 3.6.0 (2019-04-26)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.5

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] margins_0.3.23   miceadds_3.3-33  mice_3.5.0       lattice_0.20-38  randomizr_0.18.0 fabricatr_0.8.0