Summary
Objective:
Randomization is an important part of clinical trials. Using permuted-block randomization
for forcing equal group sizes potentially harms the unpredictability of treatment
assignments. This can allow bias to creep into a trial. As an alternative, Schulz
and Grimes suggest a “Mixed randomization” scheme which introduces more complexity
to realize randomization. The objective of our research was to work out a model for
randomization which is easier to handle than “Mixed randomization”, with an equal
level of performance in unpredictability and balance.
Methods:
We analyzed a “Mixed randomization” procedure regarding the degree of unpredictability
and balancing power and compared performance using permuted-block randomization with
very large block size in a worst case scenario. Our work was done by the application
of Blackwell-Hodges model for evaluation of the unpredictability of treatment assignments.
Results:
Regarding unpredictability, performance of permuted-block randomization with block
size b = 36 was very similar to that of “Mixed randomization”. Regarding balancing power
it was more favourable than “Mixed randomization”.
Conclusion:
Results of Schulz and Grimes are very important as they emphasized that mildly unequal
sample sizes of therapy groups don’t cause problems. But the suggested scheme of “Mixed
randomization” to a large extent adds complexity and we do not believe that this proposal
is very feasible. Basically, we rather recommend the use of only one restricted randomization
procedure in the best way. This can be permuted-block randomization with optimum choice
of a large block size.
Keywords
Mixed randomization scheme - balancing properties - unpredictability - block size
of permuted-block randomization
