sequentialPValueBinomialExact: Exact binomial sequential p-value for a group sequential...

In gsDesign: Group Sequential Design

Exact binomial sequential p-value for a group sequential design

Description

Computes the sequential p-value as the minimum repeated p-value over completed analyses, using [repeatedPValueBinomialExact()].

Usage

sequentialPValueBinomialExact(
  gsD,
  n.I = NULL,
  x = NULL,
  interval = c(1e-20, 0.9999),
  tol = 1e-08,
  maxiter = 100,
  check = FALSE
)

Arguments

gsD	A 'gsSurv' object with 'test.type' 1 or 4.
n.I	Increasing integer total event counts at completed analyses. If 'NULL', the planned exact binomial event counts from 'toBinomialExact(gsD)' are used. This must have at most 1 value greater than or equal to planned final events ('gsD$maxn.IPlan' if available, otherwise 'max(gsD$n.I)').
x	Integer experimental-arm event counts at the analyses in 'n.I'.
interval	Search interval for the p-values. As in [sequentialPValue()], values outside this interval are truncated to the nearest endpoint.
tol	Relative tolerance for the monotone bisection search on the alpha scale.
maxiter	Maximum number of bisection iterations for each analysis.
check	Logical. If 'TRUE', checks the monotonicity of the alpha-indexed integer efficacy bounds on a coarse grid and warns if it is violated.

Value

A single numeric one-sided sequential p-value.

See Also

[repeatedPValueBinomialExact()], [sequentialPValue()]

Examples

x <- gsSurv(
  k = 3, test.type = 4, alpha = 0.025, beta = 0.1, timing = c(0.45, 0.7),
  sfu = sfHSD, sfupar = -4, sfl = sfLDOF, sflpar = 0,
  lambdaC = 0.001, hr = 0.3, hr0 = 0.7, eta = 5e-04,
  gamma = 10, R = 16, T = 24, minfup = 8, ratio = 3
)
counts <- toBinomialExact(x)$n.I

sequentialPValueBinomialExact(gsD = x, n.I = counts, x = c(12, 23, 38))

gsDesign documentation built on July 20, 2026, 9:06 a.m.