Stratified experiments reexamined with emphasis on multicenter trials

In many stratified experiments the researcher fixes the total sample size but either cannot or does not exert control over the sample size per stratum. A classic example is a randomized, two-treatment, multicenter clinical trial-the total sample sizes per treatment group are fixed by design but the sample sizes per center are allowed to vary. Standard analyses of continuous data from such trials fail to recognize the random nature of the stratum sizes. We show that this can lead to biased inference and estimation for both so-called "type II" (unequal weighting of strata) as well as "type III" (equal weighting of strata) analyses. We propose an alternative method of analysis that explicitly accounts for the randomness of the stratum sizes and illustrate its validity using simulations. A reanalysis of published data from a 29-center clinical trial serves to reinforce the key points. (C) 2003 Elsevier Science Inc. All rights reserved.