How many time-to-event design axes are off their primary value — time_to_event_axes_off

A sensitivity analysis that varies one axis at a time only needs the designs for which this is at most one; crossing the axes simulates every combination of them as well.

Usage

time_to_event_axes_off_primary(
  control_drift,
  dropout_probability,
  event_time_distribution,
  treatment_delay = 0
)

Arguments

control_drift: Control-arm heterogeneity, kappa.
dropout_probability: Probability of loss to follow-up over the maximum follow-up time.
event_time_distribution: Either "exponential" or "weibull".
treatment_delay: Time before the treatment effect starts, in years.

Value

An integer vector, 0 for the primary design.