calgspn {MultiGroupSequential}

Calculate group-sequential p-values for multiple hypotheses

Description

calgspn() calculates the group-sequential p-values for multiple hypotheses.

Usage

calgspn(
  xm = qnorm(matrix(rep(c(0.03, 0.04, 0.01), times = 2), ncol = 3, nrow = 2)),
  alpham = matrix(rep(c(0.02, 0.03, 0.05), each = 2), ncol = 3, nrow = 2),
  critm = matrix(rep(qnorm(c(0.02, 0.03, 0.05)), each = 2), ncol = 3, nrow = 2),
  matrix.list = list(diag(3), diag(3)),
  sided = rep(-1, 2)
)

Arguments

xm

Matrix of test statistics for hypotheses (in row) and each interim (in column).

alpham

Matrix of cumulative alpha levels for the test statistics xm. Must have the same dimensions as xm. For each row, alpha levels must be

critm

Matrix of critical values for the test statistics in xm. It should be computed beforehand. Must have the same dimensions as xm.

matrix.list

List of correlation matrices corresponding to each hypothesis.

sided

Integer vector indicating the side of the test:

• -1: Reject if test statistic is smaller than or equal to the critical value (one-sided)

• 1: Reject if test statistic is greater or equal to the critical value (one-sided)

• 0: Reject if the absolute value of the test statistic is greater than the critical value (two-sided)

Value

List with element pm containing the group-sequential p-values.

Author(s)

Xiaodong Luo

Examples

calgspn(
  xm = qnorm(matrix(rep(c(0.03,0.04,0.01),times=2),ncol=3,nrow=2)),
  alpham = matrix(rep(c(0.02,0.03,0.05),each=2),ncol=3,nrow=2),
  critm = matrix(rep(qnorm(c(0.02,0.03,0.05)),each=2),ncol=3,nrow=2),
  matrix.list = list(diag(3),diag(3)),
  sided = rep(-1,2)
)