Another type of constrained randomization is called stratified randomization. Stratified randomization refers to the situation in which strata are constructed based on values of prognostic variables and a randomization scheme is performed separately within each stratum. For example, suppose that there are two prognostic variables, age and gender, such that four strata are constructed:
|Treatment A||Treatment B|
|male, age < 18||12||12|
|male, age ≥ 18||36||37|
|female, age < 18||13||12|
|female, age ≥ 18||40||40|
The strata size usually vary (maybe there are relatively fewer young males and young females with the disease of interest). The objective of stratified randomization is to ensure balance of the treatment groups with respect to the various combinations of the prognostic variables. Simple randomization will not ensure that these groups are balanced within these strata so permuted blocks are used within each stratum are used to achieve balance.
If there are too many strata in relation to the target sample size, then some of the strata will be empty or sparse. This can be taken to the extreme such that each stratum consists of only one patient each, which in effect would yield a similar result as simple randomization. Keep the number of strata used to a minimum for good effect.