title: Generating constrained randomized sequences: item frequency matters.
abstract: All experimental psychologists understand the importance of randomizing lists of items. However, randomization is generally constrained, and these constraints-in particular, not allowing immediately repeated items-which are designed to eliminate particular biases, frequently engender others. We describe a simple Monte Carlo randomization technique that solves a number of these problems. However, in many experimental settings, we are concerned not only with the number and distribution of items but also with the number and distribution of transitions between items. The algorithm mentioned above provides no control over this. We therefore introduce a simple technique that uses transition tables for generating correctly randomized sequences. We present an analytic method of producing item-pair frequency tables and item-pair transitional probability tables when immediate repetitions are not allowed. We illustrate these difficulties and how to overcome them, with reference to a classic article on word segmentation in infants. Finally, we provide free access to an Excel file that allows users to generate transition tables with up to 10 different item types, as well as to generate appropriately distributed randomized sequences of any length without immediately repeated elements. This file is freely available from http://leadserv.u-bourgogne.fr/IMG/xls/TransitionMatrix.xls.
authors.affiliation: LEAD-CNRS, University of Burgundy, Dijon, France. robert.french@u-bourgogne.fr
authors.forename: Robert M
authors.initials: RM
authors.lastname: French
authors.forename: Pierre
authors.initials: P
authors.lastname: Perruchet
mesh_terms: D000465:Algorithms; D006801:Humans; D009010:Monte Carlo Method; D011897:Random Allocation; D014584:User-Computer Interface