How many stratification factors are "too many" to use in a randomization plan?
The issue of stratification and its role in patient assignment has generated much discussion, mostly focused on its importance to a study or lack thereof. This report focuses on a much narrower problem: assuming that stratified assignment is desired, how many factors can be accommodated? This problem is investigated for two methods of balanced patient assignments; the first is based on the minimization method of Taves and the second on the commonly used method of stratified assignment. Simulation results show that the former method can accommodate a large number of factors (10-20) without difficulty but that the latter begins to fail if the total number of distinct combination of factor levels is greater than approximately n/2. The two methods are related to a linear discriminant model, which helps to explain the results.
Section of Biostatistics, Mayo Clinic, Rochester, Minnesota 55905.
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Therneau
D003201:Computers; D005260:Female; D006801:Humans; D008175:Lung Neoplasms; D008297:Male; D008962:Models, Theoretical; D011897:Random Allocation; D012107:Research Design