Experimental Design and Randomization Methods for Biomedical and Veterinary Research
ExpDesignR provides reproducible tools for treatment allocation and experimental design. Version 1.0.0 establishes the first stable API for simple, blocked, stratified, cluster, matched-pair, restricted, and covariate-adaptive randomization, together with common experimental designs and allocation utilities.
simple_randomization(100, c("Control", "Treatment"), seed = 123)
block_randomization(100, c("Control", "Treatment"), block_size = 4, seed = 123)
variable_block_randomization(100, c("Control", "Treatment"), c(4, 6, 8), seed = 123)
stratified_randomization(dat, "Sex", c("Control", "Treatment"), seed = 123)
stratified_block_randomization(dat, "Sex", c("Control", "Treatment"), 4, seed = 123)
cluster_randomization(paste0("Site_", 1:20), c("Control", "Treatment"), seed = 123)
matched_pair_randomization(dat, "Pair", c("Control", "Treatment"), seed = 123)
restricted_randomization(100, c("Control", "Treatment"), max_imbalance = 1, seed = 123)
minimization_randomization(dat, c("Sex", "Site"), seed = 123)
covariate_adaptive_randomization(dat, c("Sex", "Site"), seed = 123)completely_randomized_design(40, c("A", "B"), seed = 123)
randomized_block_design(40, c("A", "B"), block_size = 4, seed = 123)
factorial_design(list(Dose = c("Low", "High"), Diet = c("A", "B")), replicates = 3, seed = 123)
latin_square(LETTERS[1:4], seed = 123)
crossover_design(c("A", "B"), subjects = 20, periods = 2, seed = 123)allocation_summary(schedule)
plot_randomization(schedule)
export_schedule(schedule, tempfile(fileext = ".csv"))The package uses established principles of randomization and experimental design; see Rosenberger and Lachin (2015) and Jones and Kenward (2014).
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