Allocates patients to one of two treatments using Pocock and Simon's method proposed by Pocock S J, Simon R (1975) <Doi:10.2307/2529712>, by simulating covariate profiles under the assumption of independence between covariates and levels within each covariate.
PocSimMIN.sim(n = 1000, cov_num = 2, level_num = c(2, 2),
pr = rep(0.5, 4), weight = NULL, p = 0.85)the number of patients. The default is 1000.
the number of covariates. The default is 2.
the 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).
the 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 vector sum of pr should be equal to cov_num. The default is pr = rep(0.5, 4) (default), which implies that cov_num = 2 and level_num = c(2, 2).
the vector of weights for maginal imbalances. It is required that at least one element is larger than 0. If weight = NULL (default), the marginal imbalances are equally weighted as 1/cov_num for each margin.
the probability of assigning one patient to treatment 1. p should be larger than 1/2 to obtain balance. The default is 0.85.
See PocSimMIN.
See PocSimMIN.
See PocSimMIN for allocating patients with complete covariate data; See PocSimMIN.ui for the command-line user interface.