StrPBR.sim: Stratified Permuted Block Randomization with Covariate Data...

In carat: Covariate-Adaptive Randomization for Clinical Trials

Stratified Permuted Block Randomization with Covariate Data Generating Mechanism

Description

Allocates patients to one of two treatments using stratified randomization proposed by Zelen M (1974) <doi:10.1016/0021-9681(74)90015-0>, by simulating covariates-profile on assumption of independence between covariates and levels within each covariate.

Usage

StrPBR.sim(n = 1000, cov_num = 2, level_num = c(2, 2), 
           pr = rep(0.5, 4), bsize = 4)

Arguments

n	the number of patients. The default is 1000.
cov_num	the number of covariates. The default is 2.
level_num	a vector of level numbers for each covariate. Hence the length of level_num should be equal to the number of covariates. The default is c(2, 2).
pr	a vector of probabilities. Under the assumption of independence between covariates, pr is a vector containing probabilities for each level of each covariate. The length of pr should correspond to the number of all levels, and the sum of the probabilities for each margin should be 1. The default is rep(0.5, 4), which corresponds to cov_num = 2, and level_num = c(2, 2).
bsize	the block size for the stratified randomization. It is required to be a multiple of 2. The default is 4.

Details

See StrPBR.

Value

See StrPBR.

References

Ma W, Ye X, Tu F, Hu F. carat: Covariate-Adaptive Randomization for Clinical Trials[J]. Journal of Statistical Software, 2023, 107(2): 1-47.

Zelen M. The randomization and stratification of patients to clinical trials[J]. Journal of chronic diseases, 1974, 27(7): 365-375.

See Also

See StrPBR for allocating patients with complete covariate data; See StrPBR.ui for the command-line user interface.

carat documentation built on Sept. 8, 2023, 6:05 p.m.