Simulate a complete clinical trial with event data drawn from a piecewise exponential distribution

Usage

sim_comp_data(
  hazard_treatment,
  hazard_control = NULL,
  cutpoints = NULL,
  N_total,
  lambda = 0.3,
  lambda_time = NULL,
  end_of_study,
  block = 2,
  rand_ratio = c(1, 1),
  prop_loss = 0
)

Arguments

hazard_treatment: vector. Finite non-negative constant hazard rates under the treatment arm.
hazard_control: vector. Finite non-negative constant hazard rates under the control arm.
cutpoints: finite, positive, strictly increasing interior times at which the baseline hazard changes. The number of hazards for each arm must be one greater than the number of cutpoints. Default is NULL, which corresponds to a simple (non-piecewise) exponential model.
N_total: integer. Maximum sample size allowable
lambda: finite positive enrollment rates per unit time. Supply one rate for each interval defined by lambda_time. See enrollment() for the precise continuous-time process and time-origin convention.
lambda_time: NULL, or finite, positive, strictly increasing internal times at which the enrollment rate changes. The initial boundary at zero is implicit, so length(lambda) must equal length(lambda_time) + 1.
end_of_study: finite study endpoint, strictly greater than the last cutpoint.
block: scalar. Block size for generating the randomization schedule.
rand_ratio: vector. Randomization allocation for the ratio of control to treatment. Integer values mapping the size of the block. See randomization() for more details.
prop_loss: scalar. Overall proportion of subjects lost to follow-up. Subjects are selected at random for LTFU regardless of treatment assignment or event status. Each LTFU subject's observed time is drawn from a Uniform(0, t) distribution, where t is their potential event or censoring time. Since the LTFU time is always less than t, the event has not yet occurred at dropout and the subject is right-censored. Defaults to zero.

Value

A data frame with 1 row per subject and columns:

time: Time of event or censoring time.
treatment: Treatment assignment, coded 1L for the treatment arm and 0L for the control arm. Single-arm designs have treatment = 1L for every subject.
event: Indicator of whether event occurred (1L if occurred and 0L if right-censored).
enrollment: Time of patient enrollment relative to the time the trial enrolled the first patient. The package treats enrollment and randomization as occurring at the same time.
id: Identification number for each patient.
loss_to_fu: Indicator of whether the patient was lost to follow-up during observation.

Details

Enrollment is simulated directly in continuous time by enrollment(). The first patient is placed at time zero and all subsequent enrollment times are measured from first patient in. No uniform jitter is added in sim_comp_data().

lambda_time and cutpoints both contain internal change times, but they describe different clocks. lambda_time describes changes in the trial's calendar-time enrollment rate measured from first patient in. cutpoints describes changes in an individual subject's event hazard measured from that subject's enrollment. They need not have the same values or length. All time quantities supplied to a simulation should nevertheless use one common unit, such as days or months.