View source: R/rand_generatingData.R
AdjBCD.sim | R Documentation |
Allocates patients to one of two treatments based on the covariate-adjusted biased coin design as proposed by Baldi Antognini A, Zagoraiou M (2011) <doi:10.1093/biomet/asr021>, by simulating the covariates-profile under the assumption of independence between covariates and levels within each covariate.
AdjBCD.sim(n = 1000, cov_num = 2, level_num = c(2, 2),
pr = rep(0.5, 4), a = 3)
n |
the number of patients. The default is |
cov_num |
the number of covariates. The default is |
level_num |
a vector of level numbers for each covariate. Hence the length of |
pr |
a vector of probabilities. Under the assumption of independence between covariates, |
a |
a design parameter governing the degree of randomness. The default is |
See AdjBCD
.
See AdjBCD
.
Baldi Antognini A, Zagoraiou M. The covariate-adaptive biased coin design for balancing clinical trials in the presence of prognostic factors[J]. Biometrika, 2011, 98(3): 519-535.
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.
See AdjBCD
for allocating patients with complete covariate data; See AdjBCD.ui
for the command-line user interface.
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