Impact of Stratified Randomization in Clinical Trials

This paper deals with the analysis of randomization effects in clinical trials. The two randomization schemes most often used are considered: unstratified and stratified block-permuted randomization. A new analytic approach using a Poisson-gamma patient recruitment model and its further extensions is proposed. The prediction of the number of patients randomized in different strata to different treatment arms is considered. In the case of two treatments, the properties of the total imbalance in the number of patients on treatment arms caused by using stratified randomization are investigated and for a large number of strata a normal approximation of imbalance is proved. The impact of imbalance on the power of the trial is considered. It is shown that the loss of statistical power is practically negligible and can be compensated by a minor increase in sample size. The influence of patient dropout is also investigated.