Generate a Deterministic Enrollment and Dropout Schedule

Creates a time-indexed schedule with piecewise-constant enrollment and dropout rates. Every call with the same inputs returns the same schedule, so all replicates follow an identical enrollment pattern.

Usage

deterministic_schedule(
  sample_size,
  arms,
  allocation,
  enrollment,
  dropout = NULL
)

Arguments

sample_size

integer Trial sample size.

arms

character vector of arm identifiers.

allocation

numeric vector of allocation ratios.

enrollment

list with end_time (numeric period endpoints) and rate (subjects/unit time for each period).

dropout

list with end_time and rate (same structure).

Value

data.frame with columns: time (integer period), arm, enroll (subjects enrolled in that period), drop (subjects dropped). Aggregated counts - multiple subjects per row. Sorted by arm, then time.

Details

Use this when you have a well-characterized operational plan and want to isolate endpoint and analysis variability from timing variability. For a stochastic (random) schedule see stochastic_schedule().

See also

stochastic_schedule() for random inter-event times, Timer$add_schedule().

Examples

deterministic_schedule(
  sample_size = 100,
  arms = c("A", "B"),
  allocation = c(2, 1),
  enrollment = list(
    end_time = c(4, 8, 12),
    rate = c(6, 12, 18)
  ),
  dropout = list(
    end_time = c(5, 9, 13),
    rate = c(0, 3, 6)
  )
)
#>    time arm enroll drop
#> 1     1   A      4    0
#> 2     2   A      4    0
#> 3     3   A      4    0
#> 4     4   A      4    0
#> 5     5   A      8    0
#> 6     6   A      8    2
#> 7     7   A      8    2
#> 8     8   A      8    2
#> 9     9   A     12    2
#> 10   10   A      7    2
#> 11    1   B      2    0
#> 12    2   B      2    0
#> 13    3   B      2    0
#> 14    4   B      2    0
#> 15    5   B      4    0
#> 16    6   B      4    1
#> 17    7   B      4    1
#> 18    8   B      4    1
#> 19    9   B      6    1
#> 20   10   B      3    1