randomizer: 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()
)

Value

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

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

Examples

Run this code

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