Randomize cases into experimental conditions

Randomize cases into experimental conditions

randomizer(
  dataset,
  vars,
  conditions = c("A", "B"),
  blocks = NULL,
  probs = NULL,
  label = ".conditions",
  seed = 1234,
  data_filter = "",
  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")
na.rm	Remove rows with missing values (FALSE or TRUE)
envir	Environment to extract data from

Value

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

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

See also

summary.sampling to summarize results

Examples

randomizer(rndnames, "Names", conditions = c("test", "control")) %>% str()
#> List of 10
#>  $ df_name    : chr "rndnames"
#>  $ dataset    :'data.frame':	100 obs. of  2 variables:
#>   ..$ .conditions: Factor w/ 2 levels "test","control": 1 2 1 1 1 1 1 1 2 2 ...
#>   ..$ Names      : chr [1:100] "Ervin Escalona" "Allan Ammerman" "Milton Mothershed" "Deshawn Dawn" ...
#>  $ vars       : chr "Names"
#>  $ conditions : chr [1:2] "test" "control"
#>  $ blocks     : NULL
#>  $ probs      : num [1:2] 0.5 0.5
#>  $ label      : chr ".conditions"
#>  $ seed       : chr "1234"
#>  $ data_filter: chr ""
#>  $ na.rm      : logi FALSE
#>  - attr(*, "class")= chr [1:2] "randomizer" "list"