View source: R/rand_generatingData.R
DoptBCD.sim | R Documentation |
D_A
-optimal Biased Coin Design with Covariate Data Generating Mechanism
Allocates patients generated by simulating covariates-profile under the assumption of independence between covariates and levels within each covariate, to one of two treatments based on the D_A
-optimal biased coin design in the presence of prognostic factors, as proposed by Atkinson A C (1982) <doi:10.2307/2335853>.
DoptBCD.sim(n = 1000, cov_num = 2, level_num = c(2, 2),
pr = rep(0.5, 4))
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, |
See DoptBCD
.
See DoptBCD
.
Atkinson A C. Optimum biased coin designs for sequential clinical trials with prognostic factors[J]. Biometrika, 1982, 69(1): 61-67.
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 DoptBCD
for allocating patients with complete covariate data; See DoptBCD.ui
for the command-line user interface.
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