Combined the methods of alpha-stratified adaptive testing and constrained adaptive testing with shadow tests. Outlines the advantages of this approach in reducing overexposure and underexposure of items in an item pool and illustrates these advantages with an example from the Law School Admission Test. (SLD)

Presents a constrained computerized adaptive testing (CAT) algorithm that can be used to equate CAT number-correct scores to a reference test. Used an item bank from the Law School Admission Test to compare results of the algorithm with those for equipercentile observed-score equating. Discusses advantages of the approach. (SLD)

A multiple-form structure (MFS) is an ordered collection or network of testlets (i.e., sets of items). An examinee's progression through the network of testlets is dictated by the correctness of an examinee's answers, thereby adapting the test to his or her trait level. The collection of paths through the network yields the set of all possible…

Proposes a model for constrained computerized adaptive testing in which the information in the test at the trait level (theta) estimate is maximized subject to the number of possible constraints on the content of the test. Test assembly relies on a linear-programming approach. Illustrates the approach through simulation with items from the Law…

Developed a multilevel item response (IRT) model that allows for differences between the distributions of item parameters of families of item clones. Results from simulation studies based on an item pool from the Law School Admission Test illustrate the accuracy of the item pool calibration and adaptive testing procedures based on the model. (SLD)