Generate.Accrual: Create An AccrualGenerator using a power law recruitment

In scientific-computing-solutions/eventPrediction: Event Prediction in Clinical Trials with Time-to-Event Outcomes

Description

Subjects are accrued according to the c.d.f G(t)=t^k/B^k where k is a parameter, t is the time and B is the recruitment period.

See the predict from data vignette for further details

Usage

Generate.Accrual(start.date, end.date, k, deterministic = FALSE,
  rec.start.date = NULL)

Arguments

start.date	The start of the subject accrual period
end.date	The date the last subject is accrued so B = end.date - start.date unless rec.start.date is used see below
k	The non-uniformity accrual parameter
deterministic	Logical, if FALSE then the recruitment times are non-stochastically chosen so that their cumulative distribution function is G(t) otherwise they are generated by sampling random variables with a cdf G(t)
rec.start.date	If this argument is used the subjects are still recruited between start.date and end.date but they follow the cdf G(t)=(t^k-L^k)/(B^k-L^k) where t is in [L,B] and B = end.date - rec.start.date and L = start.date- rec.start.date.

Value

An AccrualGenerator object which generates the required subject accruals

scientific-computing-solutions/eventPrediction documentation built on May 29, 2019, 3:44 p.m.