01240nas a2200157   4500008004100000245006600041210006600107300001000173490000600183520071600189653003400905100001500939700001700954700001900971856009200990       1998                        eng d00aMaintaining content validity in computerized adaptive testing0 aMaintaining content validity in computerized adaptive testing  a29-410 v33 aThe authors empirically demonstrate some of the trade-offs which can occur when content balancing is imposed in computerized adaptive testing (CAT) forms or conversely, when it is ignored. The authors contend that the content validity of a CAT form can actually change across a score scale when content balancing is ignored. However they caution that, efficiency and score precision can be severely reduced by over specifying content restrictions in a CAT form. The results from 2 simulation studies are presented as a means of highlighting some of the trade-offs that could occur between content and statistical considerations in CAT form assembly. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aLuecht, RM1 aChamplain, A1 aNungester, R J  uhttp://www.iacat.org/content/maintaining-content-validity-computerized-adaptive-testing01610nas a2200133   4500008004100000245009100041210006900132300001200201490000700213520109200220653003401312100001501346856011501361       1996                        eng d00aMultidimensional computerized adaptive testing in a certification or licensure context0 aMultidimensional computerized adaptive testing in a certificatio  a389-4040 v203 a(from the journal abstract) Multidimensional item response theory (MIRT) computerized adaptive testing, building on a recent work by D. O. Segall (1996), is applied in a licensing/certification context. An example of a medical licensure test is used to demonstrate situations in which complex, integrated content must be balanced at the total test level for validity reasons, but items assigned to reportable subscore categories may be used under a MIRT adaptive paradigm to improve the reliability of the subscores. A heuristic optimization framework is outlined that generalizes to both univariate and multivariate statistical objective functions, with additional systems of constraints included to manage the content balancing or other test specifications on adaptively constructed test forms. Simulation results suggested that a multivariate treatment of the problem, although complicating somewhat the objective function used and the estimation of traits, nonetheless produces advantages from a psychometric perspective. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aLuecht, RM  uhttp://www.iacat.org/content/multidimensional-computerized-adaptive-testing-certification-or-licensure-context