randomizr is designed to make conducting field, lab, survey, or online experiments easier by automating the random assignment process.
Installation from CRAN is easy:
install.packages("randomizr")If you'd like to install the most current development release, use the following code:
install.packages("devtools")
devtools::install_github("DeclareDesign/randomizr")There are five main random assignment functions in randomizr: simple_ra(), complete_ra(), block_ra(), cluster_ra(), and block_and_cluster_ra(), which correspond to common experimental designs.
complete_ra() is the workhorse function that will be most appropriate for a large number of experimental situations: it assigns m of N units to treatment:
library(randomizr)
Z <- complete_ra(N = 100, m = 50)
table(Z)
#> Z
#> 0 1
#> 50 50A more complicated design that, for example, assigns different numbers of clusters to three different treatments can be accomodated like this:
# This makes a cluster variable: one unit in cluster "a", two in "b"...
clust_var <- rep(letters, times = 1:26)
Z <- cluster_ra(clust_var=clust_var, m_each = c(7, 7, 12),
condition_names=c("control", "placebo", "treatment"))
table(Z, clust_var)
#> clust_var
#> Z a b c d e f g h i j k l m n o p q r s t u
#> control 1 2 0 0 0 0 0 0 0 0 11 12 13 0 0 0 0 0 19 0 0
#> placebo 0 0 3 0 5 0 0 8 0 0 0 0 0 14 0 0 0 18 0 20 0
#> treatment 0 0 0 4 0 6 7 0 9 10 0 0 0 0 15 16 17 0 0 0 21
#> clust_var
#> Z v w x y z
#> control 0 0 0 25 0
#> placebo 0 0 24 0 0
#> treatment 22 23 0 0 26Happy randomizing!