lrstat (version 0.2.13)

fmodmix: Adjusted p-Values for Modified Mixture Gatekeeping Procedures

Description

Obtains the adjusted p-values for the modified gatekeeping procedures for multiplicity problems involving serial and parallel logical restrictions.

Usage

fmodmix(
  p,
  family = NULL,
  serial,
  parallel,
  gamma,
  test = "hommel",
  exhaust = TRUE
)

Value

A matrix of adjusted p-values.

Arguments

p

The raw p-values for elementary hypotheses.

family

The matrix of family indicators for the hypotheses.

serial

The matrix of serial rejection set for the hypotheses.

parallel

The matrix of parallel rejection set for the hypotheses.

gamma

The truncation parameters for each family. The truncation parameter for the last family is automatically set to 1.

test

The component multiple testing procedure. Options include "holm", "hochberg", or "hommel". Defaults to "hommel".

exhaust

Whether to use alpha-exhausting component testing procedure for the last family with active hypotheses. It defaults to TRUE.

Author

Kaifeng Lu,

References

Alex Dmitrienko, George Kordzakhia, and Thomas Brechenmacher. Mixture-based gatekeeping procedures for multiplicity problems with multiple sequences of hypotheses. Journal of Biopharmaceutical Statistics. 2016; 26(4):758–780.

George Kordzakhia, Thomas Brechenmacher, Eiji Ishida, Alex Dmitrienko, Winston Wenxiang Zheng, and David Fuyuan Li. An enhanced mixture method for constructing gatekeeping procedures in clinical trials. Journal of Biopharmaceutical Statistics. 2018; 28(1):113–128.

Examples

p = c(0.0194, 0.0068, 0.0271, 0.0088, 0.0370, 0.0018, 0.0814, 0.0066)
family = matrix(c(1, 1, 0, 0, 0, 0, 0, 0,
                  0, 0, 1, 1, 0, 0, 0, 0,
                  0, 0, 0, 0, 1, 1, 0, 0,
                  0, 0, 0, 0, 0, 0, 1, 1),
                nrow=4, byrow=TRUE)

serial = matrix(c(0, 0, 0, 0, 0, 0, 0, 0,
                  0, 0, 0, 0, 0, 0, 0, 0,
                  1, 0, 0, 0, 0, 0, 0, 0,
                  0, 1, 0, 0, 0, 0, 0, 0,
                  0, 0, 1, 0, 0, 0, 0, 0,
                  0, 0, 0, 1, 0, 0, 0, 0,
                  0, 0, 0, 0, 1, 0, 0, 0,
                  0, 0, 0, 0, 0, 1, 0, 0),
                nrow=8, byrow=TRUE)

parallel = matrix(0, 8, 8)
gamma = c(0.6, 0.6, 0.6, 1)
fmodmix(p, family, serial, parallel, gamma, test = "hommel", exhaust = TRUE)