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ExpDesignR

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.

Randomization

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)

Experimental designs

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)

Utilities

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).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.