title: Features of the sampling distribution of the ability estimate in computerized adaptive testing according to two stopping rules.
abstract: Whether paper and pencil or computerized adaptive, tests are usually described by a set of rules managing how they are administered: which item will be first, which should follow any given item, when to administer the last one. This article focus on the latter and looks at the effect of two stopping rules on the estimated sampling distribution of the ability estimate in a CAT: the number of items administered and the a priori determined size of the standard error of the ability estimate.
authors.affiliation: Department of Administration, University of Montreal, Montreal, QC, H3C 3J7, Canada. Jean-Guy.blais@umontreal.ca
authors.forename: Jean-Guy
authors.initials: JG
authors.lastname: Blais
authors.forename: Gilles
authors.initials: G
authors.lastname: Raiche
mesh_terms: D003201:Computers; D004521:Educational Measurement / Q000379:methods / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D018401:Sample Size