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Check randomisation plan

check_plan.Rd

Before committing to a randomisation plan (in terms of the number of strata, block sizes etc) it can be useful to estimate the imbalance that might be expected. This function simulates trials of a given sample size and returns the imbalance that might be expected.

Usage

check_plan(
  n_rando,
  n_strata,
  arms = c("A", "B"),
  blocksizes = c(1, 2),
  n_sim = 1000
)

# S3 method for class 'checkplan'
print(x, ...)

Arguments

n_rando

number of participants to randomise

n_strata

number of strata

arms

arms that will be randomised

blocksizes

number of each randomisation group per block (e.g. 1 = one of each arm per block, 2 = per of each arm per block)

n_sim

number of simulations

x

check_plan object

...

options passed to print.data.frame

Value

list of class checkplan with slots the same slots as input to the function plus mean (mean imbalance), counts (counts of the imbalances) and worst_case (randomisation results with the worst observed imbalance)

Functions

  • print(checkplan): Print method for check_plan output

See also

https://www.sealedenvelope.com/randomisation/simulation/

Examples


check_plan(50, 3, n_sim = 50)
#> 
#> Number of simulated trials: 50 
#>  Number of participants per trial: 50 
#>  Number of strata: 3 
#>  Blocksizes: 2, 4 
#>  Mean imbalance: 0.96 
#>  Distribution of imbalance:
#>  imbalance  n  % cum%
#>          0 27 54   54
#>          2 22 44   98
#>          4  1  2  100
#> 
#> Worst case imbalance from simulations:
#>   arm  n
#> 1   A 23
#> 2   B 27