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Quantification methods were developed for selection bias by predictability of allocations with unequal block randomization
Authors:Dupin-Spriet Thérèse  Fermanian Jacques  Spriet Alain
Affiliation:

aLaboratoire de pharmacologie, de pharmacocinétique et de pharmacie clinique, Faculté de Pharmacie, 3 rue du Professeur Laguesse, B.P. 83, F59006 Lille Cedex, France

bDépartement de Statistique, Faculté de Médecine et Hôpital Necker-Enfants Malades, Paris, France

cAlain Spriet conseil, Paris, France

Abstract:BACKGROUND AND 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. STUDY DESIGN AND SETTING: 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.
Keywords:Clinical trials   Selection bias   Randomization   Blocks   Predictability
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