Function reference • OptimalGoldstandardDesigns

All functions

OptimalGoldstandardDesigns OptimalGoldstandardDesigns-package: OptimalGoldstandardDesigns

calc_ASN(): Helper function to calculate the average sample size

calc_ASNP(): Calculate the average placebo group sample size

calc_Sigma(): Helper function to calculate the covariance matrix from the group variances, cumulative allocation ratios and gamma factors

calc_c(): Helper function to calculate allocation ratios from stagewise sample sizes

calc_conditional_local_rejection_probs(): Calculate the (local) conditional type I errors of both hypothesis given both interim test statistics.

calc_conditional_power(): Calculate the conditional power to reject both hypothesis given both interim test statistics.

calc_cumc(): Helper function to calculate "cumulative allocation ratio" from stagewise allocation ratios

calc_cumn(): Helper function to calculate cumulative sample sizes from stagewise sample sizes

calc_final_state_probs(): Helper function to calculate the final state probabilities

calc_gamma(): Helper function to calculate gamma factors from group variances and cumulative allocation ratios

calc_local_alphas(): Helper function to calculate the local type I error rates of a Design

calc_local_rejection_boundaries(): Helper function to calculate the local rejection boundaries of group sequential testing procedure associated with the hypothesis belong to the groups argument

calc_mu_vec(): Helper function to calculate expected value of normal test statistic vector c(Z_TP1, Z_TP2, Z_TC1, Z_TP2) under the null and alternative hypothesis given nT1, gamma and mu.

calc_mu_wo_nT1(): Helper function to calculate expected value of normal test statistic vector c(Z_TP1, Z_TP2, Z_TC1, Z_TP2) under the null and alternative hypothesis given nT1=1, gamma and mu.

calc_nT1_wrt_bTC2e(): Helper function to calculate the required sample size (of the stage 1 treatment group) to achieve the target power given the bTC2e

calc_n_from_c(): Helper function to calculate other n's given n_1,T and allocation ratios

calc_prob_reject_both(): Helper function to calculate the probability to reject both hypotheses given the mean of the normal test statistic vector c(Z_TP1, Z_TP2, Z_TC1, Z_TC2).

calc_prob_reject_both_singlestage(): Helper function to calculate the probability to reject both hypotheses given the mean of the normal test statistic vector c(Z_TP1, Z_TC1).

calc_worst_type_I_error(): Helper function to calculate the maximal probability of rejecting the non-inferiority hypothesis in the testing procedure featuring nonsequential futility, given a point hypothesis for the superiority hypothesis.

conditional_Sigma(): Calculate the conditional mean of a multivariate normal distribution

conditional_mean(): Calculate the conditional mean of a multivariate normal distribution

objective_onestage(): Objective function for single-stage gold-standard designs

objective_twostage(): Objective function for two-stage gold-standard designs

optimize_design_onestage(): Calculate optimal design parameters for a single-stage gold-standard design

optimize_design_twostage(): Calculate optimal design parameters for a two-stage gold-standard design

padd_whitespace(): Add whitespace padding to string

pmvnorm_(): mvtnorm::pmvnorm, but returns 0 if any lower boundary is larger than any upper boundary

pmvt_(): mvtnorm::pmvt, but returns 0 if any lower boundary is larger than any upper boundary

print(<OneStageGoldStandardDesign>): Printing method for optimal single-stage goldstandard designs

print(<TwoStageGoldStandardDesign>): Printing method for optimal two-stage goldstandard designs