randomizer {radiant.design}

Randomize cases into experimental conditions

Description

Randomize cases into experimental conditions

Usage

randomizer(
  dataset,
  vars,
  conditions = c("A", "B"),
  blocks = NULL,
  probs = NULL,
  label = ".conditions",
  seed = 1234,
  data_filter = "",
  arr = "",
  rows = NULL,
  na.rm = FALSE,
  envir = parent.frame()
)

Arguments

dataset

Dataset to sample from

vars

The variables to sample

conditions

Conditions to assign to

blocks

A vector to use for blocking or a data.frame from which to construct a blocking vector

probs

A vector of assignment probabilities for each treatment conditions. By default each condition is assigned with equal probability

label

Name to use for the generated condition variable

seed

Random seed to use as the starting point

data_filter

Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")

arr

Expression to arrange (sort) the data on (e.g., "color, desc(price)")

rows

Rows to select from the specified dataset

na.rm

Remove rows with missing values (FALSE or TRUE)

envir

Environment to extract data from

Details

Wrapper for the complete_ra and block_ra from the randomizr package. See https://radiant-rstats.github.io/docs/design/randomizer.html for an example in Radiant

Value

A list of variables defined in randomizer as an object of class randomizer

See Also

summary.sampling to summarize results

Examples

randomizer(rndnames, "Names", conditions = c("test", "control")) %>% str()