R package for Design of Randomized Experiments
blockTools blocks units into experimental blocks with one unit per treatment condition by creating a measure of multivariate distance between all possible pairs of units. Users can set the maximum, minimum, or an allowable range of differences between units on one variable. blockTools also randomly assigns units to treatment conditions, and can diagnose potential interference between units assigned to different treatment conditions. Users can write outputs to .tex and .csv files.
After installation (see below), at the R prompt:
library(blockTools)
# load the example data:
data(x100)
# create blocked pairs:
out <- block(x100, id.vars = "id", block.vars = c("b1", "b2"))
# assign one member of each pair to treatment/control:
assg <- assignment(out)
# detect unit pairs with different treatment assignments
# that are within 1 unit of each other on variable "b1":
diag <- diagnose(assg, x100, id.vars = "id", suspect.var = "b1", suspect.range = c(0, 1))
To view the results:
# The blocked pairs:
out$blocks
# The assigned pairs:
assg
# Those pairs with small distances on "b1" between them:
diag
Install blockTools with
install.packages("blockTools")
If you have access to the private repository, this package can be installed via
devtools::install_github("ryantmoore/blockTools",
auth_token = "<your PAT for this private repo>")