title: Quantification methods were developed for selection bias by predictability of allocations with unequal block randomization.
abstract: OBJECTIVE
  A selection of patients for a controlled clinical trial may be biased because of prior knowledge of the treatment. With randomized blocks of known or guessed lengths, some allocations can be predicted with certainty. Previously described methods determine the proportion of predictable cases for blocks of equal lengths. It may be useful to make a calculation for unequal blocks as well to find a method that reduces this predictability.
  
  
  METHODS
  Quantification methods are developed for series of two and three unequal blocks, using the probability of identifying a long block when it comes before a short one if it starts with a sequence incompatible with the content of a short block. Results are compared with the recently described maximal allocation procedure.
  
  
  RESULTS
  Predictability is not always reduced by unequal blocks and is even worse in some cases, compared to equal blocks. Predictability is not necessarily decreased with the maximal allocation procedure.
  
  
  CONCLUSIONS
  Before choosing an allocation method, it is important to quantify the predictability of possible options to reduce selection bias. Several practical recommendations are formulated for choosing methods, taking this risk of bias into account.
authors.affiliation: Laboratoire de pharmacologie, de pharmacocinétique et de pharmacie clinique, Faculté de Pharmacie, Lille, France. therese.spriet@univ-lille2.fr
authors.forename: Thérèse
authors.initials: T
authors.lastname: Dupin-Spriet
authors.forename: Jacques
authors.initials: J
authors.lastname: Fermanian
authors.forename: Alain
authors.initials: A
authors.lastname: Spriet
mesh_terms: D005544:Forecasting; D006801:Humans; D018579:Patient Selection; D011897:Random Allocation; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D015983:Selection Bias