
Exact binomial sequential p-value for a group sequential design
Source:R/binomialExactPValues.R
sequentialPValueBinomialExact.RdComputes 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.
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))
#> [1] 0.008683036