Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods

9.4 Covariate-Adaptive Randomization

9.4.1 Stratified Randomization

Prior to randomization, there are often some baseline prognostic factors (covariates) collected, such as age, gender, and disease severity, which may have an important impact on the treatment outcomes. It is thus desirable to balance treatment allocation over these covariates so that valid and efficient treatment comparisons can be conducted.

The simplest way to balance the treatment assignment over important covariates is through stratification. As shown in Figure 9.1 Illustration of Stratified Randomization, trial participants are first grouped into mutually exclusive strata based on the values of their prognostic variables, and then they are randomly allocated to each treatment ...