How many stratification factors are "too many" to use in a randomization plan?

Research output: Contribution to journalArticlepeer-review

100 Scopus citations


The issue of stratification and its role in patient assignment has generated much discussion, mostly focused on its importance to a study [1,2] or lack thereof [3,4]. 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 [5] and the second on the commonly used method of stratified assignment [6,7]. Stimulation 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.

Original languageEnglish (US)
Pages (from-to)98-108
Number of pages11
JournalControlled Clinical Trials
Issue number2
StatePublished - Apr 1993


  • Accidental bias
  • adaptive allocation
  • clinical trial design
  • randomization
  • stratification
  • treatment imbalance

ASJC Scopus subject areas

  • Pharmacology


Dive into the research topics of 'How many stratification factors are "too many" to use in a randomization plan?'. Together they form a unique fingerprint.

Cite this