lrstat (version 0.3.3)

fCERNewBound: Compute new stage-wise bounds after adaptation

Description

Compute new stage 2 bounds after an adaptation of the hypotheses tested or their weights.

Usage

fCERNewBound(
  stg1_p,
  wgtmat,
  family = NULL,
  corr = NULL,
  stg1_inthyp_nr_idx,
  CER,
  stg2_elemhyp_idx,
  stg2_wgtmat,
  info_frac_new,
  nthreads = 0
)

Value

A list containing:

• inthyp: The indicator matrix of the adapted intersection hypotheses.

• stg2_coef_new: The new stage 2 coefficient for each adapted intersection hypothesis.

• stg2_bnd_new: The new stage 2 bounds for the elementary hypotheses in each adapted intersection hypothesis.

Arguments

stg1_p

P-values for the elementary hypotheses in stage 1.

wgtmat

Weight matrix for the original intersection hypotheses.

family

Family matrix indicating which hypotheses belong to which families. If NULL, all hypotheses are assumed to belong to the same family.

corr

Correlation matrix for the test statistics.

stg1_inthyp_nr_idx

Indices of the intersection hypotheses not rejected in stage 1.

CER

Conditional error rates for the intersection hypotheses.

stg2_elemhyp_idx

Indices of the elementary hypotheses in stage 2.

stg2_wgtmat

Weight matrix for the intersection hypotheses in stage 2.

info_frac_new

New information fraction for stage 1 after adaptation.

nthreads

The number of threads to use in simulations (0 means the default RcppParallel behavior).

Author

Kaifeng Lu,

References

Cyrus Mehta, Ajoy Mukhopadhyay, and Martin Posch. Graph Based, Adaptive, Multiarm, Multiple Endpoint, Two-Stage Designs. Statistics in Medicine. 2025.

Examples

initial_weights <- c(0.5, 0.5, 0, 0)
transition_matrix <- matrix(c(0, 0.5, 0.5, 0,
                              0.5, 0, 0, 0.5,
                              0, 1, 0, 0,
                              1, 0, 0, 0),
                            nrow = 4, byrow = TRUE)
wgtmat <- fwgtmat(initial_weights, transition_matrix)
family <- matrix(c(1, 1, 0, 0,
                   0, 0, 1, 1),
                 nrow = 2, byrow = TRUE)
corr <- matrix(c(1, 0.5, NA, NA,
                 0.5, 1, NA, NA,
                 NA, NA, 1, 0.5,
                 NA, NA, 0.5, 1),
               nrow = 4, byrow = TRUE)
stage1_pvalues <- c(0.00045, 0.0952, 0.0225, 0.1104)
bounds <- fCERStageBound(
  wgtmat, family, corr, alpha = 0.025,
  alpha1 = errorSpent(0.5, 0.025, "sfOF"),
  info_frac = 0.5, nthreads = 1)
conditional_error_rates <- fCERCer(
  stage1_pvalues, wgtmat, family, corr, info_frac = 0.5,
  bounds$stg1_bnd, bounds$stg2_bnd, nthreads = 1)
stage2_weight_matrix <- fwgtmat(
  w = c(0.5, 0.5),
  G = matrix(c(0, 1, 1, 0), 2, 2, byrow = TRUE))
fCERNewBound(stage1_pvalues, wgtmat, family, corr,
             conditional_error_rates$stg1_inthyp_nr_idx,
             conditional_error_rates$CER,
             stg2_elemhyp_idx = c(2, 4),
             stage2_weight_matrix, info_frac_new = 0.4,
             nthreads = 1)