01899nas a2200193   4500008004100000020002200041245010000063210006900163260004300232300001200275490000700287520117500294653002301469653003001492653002301522653002501545100001601570856011901586       2004                        eng d  a1076-9986 (Print)00aEstimating ability and item-selection strategy in self-adapted testing: A latent class approach0 aEstimating ability and itemselection strategy in selfadapted tes  bAmerican Educational Research Assn: US  a379-3960 v293 aThis article presents a psychometric model for estimating ability and item-selection strategies in self-adapted testing. In contrast to computer adaptive testing, in self-adapted testing the examinees are allowed to select the difficulty of the items. The item-selection strategy is defined as the distribution of difficulty conditional on the responses given to previous items. The article shows that missing responses in self-adapted testing are missing at random and can be ignored in the estimation of ability. However, the item-selection strategy cannot always be ignored in such an estimation. An EM algorithm is presented to estimate an examinee's ability and strategies, and a model fit is evaluated using Akaike's information criterion. The article includes an application with real data to illustrate how the model can be used in practice for evaluating hypotheses, estimating ability, and identifying strategies. In the example, four strategies were identified and related to examinees' ability. It was shown that individual examinees tended not to follow a consistent strategy throughout the test. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aestimating ability10aitem-selection strategies10apsychometric model10aself-adapted testing1 aRevuelta, J  uhttp://iacat.org/content/estimating-ability-and-item-selection-strategy-self-adapted-testing-latent-class-approach