blockTools-package | R Documentation |
Block units into experimental blocks, with one unit per treatment condition, by creating a measure of multivariate distance between all possible pairs of units. Maximum, minimum, or an allowable range of differences between units on one variable can be set. Randomly assign units to treatment conditions. Diagnose potential interference problems between units assigned to different treatment conditions. Write outputs to .tex and .csv files.
Given raw data, block
creates experimental blocks, assignment
assigns units to treatment conditions, diagnose
detects possible interference problems, and outTeX
and outCSV
write block or assignment output objects to a set of .tex and .csv files, respectively. In sequential experiments, seqblock
assigns units to treatment conditions.
Ryan T. Moore [aut, cre] (rtm@american.edu), Keith Schnakenberg [aut] (keith.schnakenberg@gmail.com)
https://www.ryantmoore.org/html/software.blockTools.html
Moore, Ryan T. Multivariate Continuous Blocking to Improve Political Science Experiments. Political Analysis, 20(4):460-479, 2012.
Moore, Ryan T. and Sally A. Moore. Blocking for Sequential Political Experiments. Political Analysis, 21(4):507-523, 2013.
Useful links:
data(x100)
# block
out <- block(x100, groups = "g", n.tr = 2, id.vars = c("id"),
block.vars = c("b1", "b2"), algorithm = "optGreedy",
distance = "mahalanobis", level.two = FALSE, valid.var = "b1",
valid.range = c(0,500), verbose = TRUE)
# assign
assg <- assignment(out, seed = 123)
# diagnose
diag <- diagnose(object = assg, data = x100, id.vars = "id",
suspect.var = "b2", suspect.range = c(0,50))
# create .tex files of assigned blocks
# outTeX(assg)
# create .csv files of unassigned blocks
# outCSV(out)
# create block IDs
createBlockIDs(out, x100, id.var = "id")
# block ID integers are unique, even with several groups
axb <- assg2xBalance(assg, x100, id.var = "id", bal.vars = c("b1", "b2"))
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