Group-randomized study designs are useful when individually-randomized designs either are not possible, or will not be able to estimate the parameters of interest. Group-randomized trials often have small number of experimental units or groups and strong geographically-induced between-unit correlation, thereby increasing the chance of obtaining a "bad" randomization outcome. It has been suggested to highly constrain the design through restriction to those allocations that meet specified criteria based on certain covariates available at the baseline. We describe a SAS® macro that allocates treatment conditions in a two-arm stratified group-randomized design that ensures balance on relevant covariates. The application of the macro is illustrated using two examples of group-randomized designs.
- Constrained randomization
- Stratified group-randomized trial
ASJC Scopus subject areas
- Computer Science Applications
- Health Informatics