run_simulations_2x2_rom: Run Simulations for a 2x2 Crossover Design with Ratio of...

In SimTOST: Sample Size Estimation for Bio-Equivalence Trials Through Simulation

Run Simulations for a 2x2 Crossover Design with Ratio of Means (ROM) test

Description

This function simulates a 2x2 crossover trial across multiple iterations. It evaluates equivalence across multiple endpoints using the Ratio of Means (ROM) test.

Usage

run_simulations_2x2_rom(
  nsim,
  n,
  muT,
  muR,
  SigmaW,
  lequi_tol,
  uequi_tol,
  alpha,
  sigmaB,
  dropout,
  Eper,
  Eco,
  typey,
  adseq,
  k,
  arm_seed
)

Arguments

nsim	Integer. The number of simulations to run.
n	Integer. The sample size per period.
muT	Numeric vector. Mean outcomes for the active treatment.
muR	Numeric vector. Mean outcomes for the reference treatment.
SigmaW	Numeric matrix. Within-subject covariance matrix for endpoints.
lequi_tol	Numeric vector. Lower equivalence thresholds for each endpoint.
uequi_tol	Numeric vector. Upper equivalence thresholds for each endpoint.
alpha	Numeric vector. Significance levels for hypothesis testing across endpoints.
sigmaB	Numeric. Between-subject variance for the crossover model.
dropout	Numeric vector of size 2. Dropout rates for each sequence.
Eper	Numeric vector. Expected period effects for each sequence.
Eco	Numeric vector. Expected carryover effects for each sequence.
typey	Integer vector indicating the classification of each endpoint, where 1 corresponds to a primary endpoint and 2 corresponds to a secondary endpoint.
adseq	Logical. If TRUE, applies sequential (hierarchical) testing.
k	Integer. Minimum number of endpoints required for equivalence.
arm_seed	Integer vector. Random seed for each simulation.

Details

This function evaluates equivalence using the Ratio of Means (ROM) test. Equivalence is determined based on predefined lower lequi_tol and upper uequi_tol equivalence thresholds, and hypothesis testing is conducted at the specified significance level alpha. If adseq is TRUE, primary endpoints must establish equivalence before secondary endpoints are evaluated. The sample size per period is adjusted based on dropout rates, ensuring valid study conclusions. The simulation incorporates within-subject correlation using SigmaW and accounts for between-subject variance with sigmaB. Expected period effects Eper and carryover effects Eco are included in the model. A fixed random seed arm_seed is used to ensure reproducibility across simulations.//'

Value

A numeric matrix where each column stores simulation results: The first row (totaly) represents the overall equivalence decision (1 = success, 0 = failure). Subsequent rows contain equivalence decisions per endpoint, mean estimates for the treatment group, mean estimates for the reference group, standard deviations for treatment, and standard deviations for reference.

@author Thomas Debray [e-mail]

SimTOST documentation built on April 3, 2025, 9:05 p.m.