findSCdesigns {curtailment}

findSCDesigns

Description

This function finds admissible design realisations for single-arm binary outcome trials, using stochastic curtailment. This function differs from singlearmDesign in that it includes a Simon-style interim analysis after some n1 participants. The output is a data frame of admissible design realisations.

Usage

findSCdesigns(
  nmin,
  nmax,
  p0,
  p1,
  alpha,
  power,
  minthetaE = p1,
  maxthetaF = p1,
  bounds = "wald",
  fixed.r1 = NA,
  fixed.r = NA,
  fixed.n1 = NA,
  max.combns = 1e+06,
  maxthetas = NA,
  exact.thetaF = NA,
  exact.thetaE = NA,
  progressBar = FALSE
)

Arguments

nmin

Minimum permitted sample size.

nmax

Maximum permitted sample size.

p0

Probability for which to control the type-I error-rate

p1

Probability for which to control the power

alpha

Significance level

power

Required power (1-beta).

minthetaE

Minimum value of upper threshold theta_E_min. Defaults to p.

maxthetaF

Maximum value of lower CP threshold theta_F_max. Defaults to p.

bounds

choose what final rejection boundaries should be searched over: Those of A'Hern ("ahern"), Wald ("wald") or no constraints (NA). Defaults to "wald".

fixed.r1

Choose what interim rejection boundaries should be searched over. Useful for reproducing a particular design realisation. Defaults to NA.

fixed.r

Choose what final rejection boundaries should be searched over. Useful for reproducing a particular design realisation. Defaults to NA.

fixed.n1

Choose what interim sample size values n1 should be searched over. Useful for reproducing a particular design realisation. Defaults to NA.

max.combns

Provide a maximum number of ordered pairs (theta_F, theta_E). Defaults to 1e6.

maxthetas

Provide a maximum number of CP values used to create ordered pairs (theta_F, theta_E). Can be used instead of max.combns. Defaults to NA.

exact.thetaF

Provide an exact value for lower threshold theta_F. Useful for reproducing a particular design realisation. Defaults to NA.

exact.thetaE

Provide an exact value for upper threshold theta_E. Useful for reproducing a particular design realisation. Defaults to NA.

progressBar

Logical. If TRUE, shows progress bar. Defaults to FALSE.

Value

Output is a list of two dataframes. The first, $input, is a one-row data frame that contains important arguments used in the call. The second, $all.des,contains the operating characteristics of all admissible designs found.

Examples

findSCdesigns(nmin = 20, nmax = 20, p0 = 0.1, p1 = 0.4, power = 0.8, alpha = 0.1, max.combns=1e2)