Minimization randomization to k treatment groups

Description

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

Usage

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

Arguments

Value

treatment assignment for the jth subject

References

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.

Examples

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")

Blocked randomization

Description

The fuction is used to generate treatment assignments based on blocked randomization.

Usage

blkrandomization(n, blocksize, block)

Arguments

Value

trt a sequence of treatment assignments

Examples

blocksize <- 4
block <- c(1, 2, 3, 4) # treatment 1, 2, 3, 4
n <- 35
blkrandomization(n, blocksize, block)

Displays the number of randomized subjects at each level for all covariate factors.

Description

The fuction to cound the number of randomized subjects at each level for all covariate factors

Usage

randbalance(trt, covmat, ntrt, trtseq)

Arguments

Value

the number of randomized subjects at each level for all covariate factors

Calculates the total imbalance measured by minimization algorithms.

Description

The function to calculates the total imbalance measured by minimization algorithms

Usage

totimbal(trt = trt, covmat = covmat, covwt = covwt, ratio = ratio,
  ntrt = ntrt, trtseq = trtseq, method = "Range")

Arguments

Value

total imbalance