Investigate how block sizes and strata affect imbalance

Perform simulations to help you decide on the best block sizes to use in your trial.
If you are using random permuted blocks, you need to
decide on the block size (or sizes) to use.
If the block size is small, and the trial is unblinded, it may be possible for
investigators to guess the next treatment allocation. But if the block size is large,
or you have many strata, the trial may end with many incomplete blocks. This increases
the chance there will be imbalance in the number allocated to each treatment.

How does this work?

When you run the simulations, a stratified randomisation list is generated
using the treatment groups, block sizes, number of strata and sample size you have
specified. To keep things simple, it is assumed that each stratum will receive
approximately the same number of randomisations. Then the number randomised to
each treatment group using this list is calculated, and the imbalance is recorded.
This process is repeated thousands of times (as specified by the number of
replications you chose) and the results aggregated.

Source code

The JavaScript source code used for these simulations is open source and is
published here.

Kernan WN, Viscoli CM, Makuch RW, Brass LM, Horwitz RI. Stratified randomization for clinical trials. J Clin Epidemiol; 1999.

Results

The results of the simulations will be shown below. The imbalance is calculated at the
end of each trial, assuming it met its target sample size and that randomisations
were approximately evenly spread across the strata. Imbalance is the sum of the
differences in the number randomised to each group overall compared to the optimum
number if the trial was perfectly balanced.