sim_subjects: Simulate subjects

In taylordunn/gasr: Simulate and Analyze Goal Attainment Scaling Data

Simulate subjects

Description

Simulate a number of subjects with subject-level random effects, and randomly assign them to groups.

Usage

sim_subjects(
  n_subjects = 100,
  sigma_u = 0.5,
  group_allocation = list(control = 0.5, treatment = 0.5),
  random_allocation = TRUE
)

Arguments

n_subjects	Number of subjects.
sigma_u	Standard deviation of the subject-level random effect.
group_allocation	A named list of groups and their probability of assignment. By default, will give equal probability to "control" and "treatment" groups. If NULL, will returns subjects without groups.
random_allocation	Logical. If TRUE (default), randomly assigns to groups based on probabilities in group_allocation. If FALSE, assigns with equal probability. Note that this option will return an error if the subjects cannot be neatly divided. For example, n_subjects = 21 with two groups of probabilities 0.5 and 0.5, will return an error if random_allocation = FALSE because 21 cannot be equally divided in two.

Value

A data frame with a row for each subject.

Examples

sim_subjects(n_subjects = 20)
sim_subjects(
  group_allocation = list("placebo" = 1/2,
                          "1x dose" = 1/4, "2x dose" = 1/4)
)

# If using non-random group allocation, `n_subjects` must be able to be
#  divided using the given `group_allocation`
sim_subjects(
  n_subjects = 99,
  group_allocation = list("placebo" = 1/3,
                          "1x dose" = 1/3, "2x dose" = 1/3),
  random_allocation = FALSE
)

taylordunn/gasr documentation built on April 5, 2022, 1:37 a.m.