# mergedblocksmulti

##### Merged block randomization for multiple strata

Function to carry out merged block randomization, for multiple strata.

##### Usage

```
mergedblocksmulti(K, n, ratio = c(1, 1),
labels = as.character(1:length(ratio)))
```

##### Arguments

- K
The number of strata.

- n
The number of subjects to randomize. May be given as a single number, for the same number of subjects per stratum, or as a vector or length

`K`

in case the desired sample size varies per stratum- ratio
The desired randomization ratio, given as a vector. Default is 1:1 randomization, but more groups or unequal ratios are possible as well. E.g. for 1:1:2 randomization, use c(1, 1, 2).

- labels
The labels for the assignments, given as a vector, e.g. c("treatment", "placebo"). The length of

`labels`

should match the length of`ratio`

. Default is to use numeric labels.

##### Value

Allocation of the subjects, given as a dataframe, with one column per stratum. Padded with NAs in case of different sample sizes per stratum.

##### References

S.L. van der Pas (2019). Merged block randomisation: a novel randomisation procedure for small clinical trials. Clinical Trials. Pages tba.

##### See Also

`mergedblocks`

for a version for a single stratum.

##### Examples

```
# NOT RUN {
#Four strata, randomize 20 patients for each stratum, 1:1 allocation,
#with labels "0" and "1".
mergedblocksmulti(K = 4, n = 20)
#Three strata, randomize 30, 40 and 50 patients for each stratum,
#1:2 allocation, with labels "placebo" and "treatment".
mergedblocksmulti(K = 3, n = c(30, 40, 50), ratio = c(1, 2), labels = c("placebo", "treatment"))
# }
```

*Documentation reproduced from package mergedblocks, version 1.0.0, License: GPL-3*