computeLogrankBetaFrom {safestats}

Helper function: Computes the type II error under optional stopping based on the minimal clinically relevant hazard ratio and the maximum number of nEvents.

Description

Helper function: Computes the type II error under optional stopping based on the minimal clinically relevant hazard ratio and the maximum number of nEvents.

Usage

computeLogrankBetaFrom(
  hrMin,
  nEvents,
  m0 = 50000L,
  m1 = 50000L,
  alpha = 0.05,
  alternative = c("twoSided", "greater", "less"),
  nSim = 1000L,
  nBoot = 10000L,
  groupSizePerTimeFunction = returnOne,
  parameter = NULL,
  pb = TRUE
)

Arguments

hrMin

numeric that defines the minimal relevant hazard ratio, the smallest hazard ratio that we want to detect.

nEvents

numeric > 0, targetted number of events.

m0

Number of subjects in the control group 0/1 at the beginning of the trial, i.e., nPlan[1].

m1

Number of subjects in the treatment group 1/2 at the beginning of the trial, i.e., nPlan[2].

alpha

numeric in (0, 1) that specifies the tolerable type I error control –independent on n– that the designed test has to adhere to. Note that it also defines the rejection rule e10 > 1/alpha.

alternative

a character string specifying the alternative hypothesis, which must be one of "twoSided" (default),"greater" or "less". The alternative is pitted against the null hypothesis of equality of the survival distributions. More specifically, let lambda1 be the hazard rate of group 1 (i.e., placebo), and lambda2 the hazard ratio of group 2 (i.e., treatment), then the null hypothesis states that the hazard ratio theta = lambda2/lambda1 = 1. If alternative = "less", the null hypothesis is compared to theta < 1, thus, lambda2 < lambda1, that is, the hazard of group 2 (i.e., treatment) is less than that of group 1 (i.e., placebo), hence, the treatment is beneficial. If alternative = "greater", then the null hypothesis is compared to theta > 1, thus, lambda2 > lambda1, hence, harm.

nSim

integer > 0, the number of simulations needed to compute power or the number of events for the exact safe logrank test under continuous monitoring

nBoot

integer > 0 representing the number of bootstrap samples to assess the accuracy of the approximation of power or nEvents for the exact safe logrank test under continuous monitoring

groupSizePerTimeFunction

A function without parameters and integer output. This function provides the number of events at each time step. For instance, if rpois(1, 7) leads to a random number of events at each time step.

parameter

Numeric > 0, represents the safe tests defining thetaS. Default NULL so it's decided by the algorithm, typically, this equals hrMin, which corresponds to the GROW choice.

pb

logical, if TRUE, then show progress bar.

Value

a list which contains at least beta and an adapted bootObject of class boot.

Author(s)

Muriel Felipe Perez-Ortiz and Alexander Ly

Examples

computeLogrankBetaFrom(hrMin=0.7, 300, nSim=10)