Nonlinear sequential designs for logistic item response theory models with applications to computerized adaptive tests

Computerized adaptive testing is becoming increasingly popular due to advancement of modern computer technology. It differs from the conventional standardized testing in that the selection of test items is tailored to individual examinee's ability level. Arising from this selection strategy is a nonlinear sequential design problem. We study, in this paper, the sequential design problem in the context of the logistic item response theory models. We show that the adaptive design obtained by maximizing the item information leads to a consistent and asymptotically normal ability estimator in the case of the Rasch model. Modifications to the maximum information approach are proposed for the two- and three-parameter logistic models. Similar asymptotic properties are established for the modified designs and the resulting estimator. Examples are also given in the case of the two-parameter logistic model to show that without such modifications, the maximum likelihood estimator of the ability parameter may not be consistent.Comment: Published in at http://dx.doi.org/10.1214/08-AOS614 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Gauge mediation with heavy doublet superparticles

It is challenging for supersymmetry if the 125 GeV Higgs boson is confirmed by the LHC. In the case of small squark mixing it is inevitable to introduce heavy top squarks to lift the Higgs mass that is hard to be produced by the LHC. Here we consider the possibility that in gauge mediation the superparticles belonging to SU(2) doublets are much heavier than those do not carry the SU(2) quantum numbers. Under the assumption not only the Higgs mass can be large enough but also there are light right handed top squarks below the TeV scale that can be observed in future.Comment: 10pages, no figures, accepted for publication in Phys. Rev.