Description Usage Arguments Value References Examples

The function is used to generate treatment assignment by minimization algorithms.

1 2 | ```
Minirand(covmat = covmat, j, covwt = covwt, ratio = ratio,
ntrt = ntrt, trtseq = trtseq, method = "Range", result = res, p)
``` |

`covmat` |
matrix or data frame of covariate factors |

`j` |
the jth subject in the randomization sequence |

`covwt` |
vector of weights of the covaraite factors |

`ratio` |
vector of randomization ratios for each treatment |

`ntrt` |
numeric number of treatment groups |

`trtseq` |
vector of a sequence of treatment groups |

`method` |
the method or algorithm for the minimization randomization |

`result` |
the treatment assignments in subjetcs achieved so far |

`p` |
the high probability for new assignment |

treatment assignment for the jth subject

Pocock and Simon (1975), Sequential Treatment Assignment with Balancing for Prognostic Factors in the Controlled Clinical Trial. Biometrics; 103-115.

Jin, Polis, and Hartzel (2019), "Algorithms for minimization randomization and the implementation with an R package". Communications in Statistics-Simulation and Computation; May 2019.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
ntrt <- 3
nsample <- 120
trtseq <- c(1, 2, 3)
ratio <- c(2, 2, 1)
c1 <- sample(seq(1, 0), nsample, replace = TRUE, prob = c(0.4, 0.6))
c2 <- sample(seq(1, 0), nsample, replace = TRUE, prob = c(0.3, 0.7))
c3 <- sample(c(2, 1, 0), nsample, replace = TRUE, prob = c(0.33, 0.2, 0.5))
c4 <- sample(seq(1, 0), nsample, replace = TRUE, prob = c(0.33, 0.67))
covmat <- cbind(c1, c2, c3, c4) # generate the matrix of covariate factors for the subjects
# label of the covariates
colnames(covmat) = c("Gender", "Age", "Hypertension", "Use of Antibiotics")
covwt <- c(1/4, 1/4, 1/4, 1/4) #equal weights
res <- rep(100, nsample) # result is the treatment needed from minimization method
#gernerate treatment assignment for the 1st subject
res[1] = sample(trtseq, 1, replace = TRUE, prob = ratio/sum(ratio))
for (j in 2:nsample)
{
# get treatment assignment sequentiall for all subjects
res[j] <- Minirand(covmat=covmat, j, covwt=covwt, ratio=ratio,
ntrt=ntrt, trtseq=trtseq, method="Range", result=res, p = 0.9)
}
trt1 <- res
#Display the number of randomized subjects at covariate factors
balance1 <- randbalance(trt1, covmat, ntrt, trtseq)
balance1
totimbal(trt = trt1, covmat = covmat, covwt = covwt,
ratio = ratio, ntrt = ntrt, trtseq = trtseq, method = "Range")
``` |

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