University of Illinois at Urbana-Champaign

Current Areas of Research

• Cognitive Diagnosis

• Test Bias

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• Dimensionality Assessment

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• Large Sample Theory for Latent Variable Models

In addition to developing new tools for data analysis, past and current members of the lab have engaged in theoretical analyses of the asymptotic properties of various procedures, models, and statistics. Examples include large sample theory for DETECT, DIMTEST, nonparametric ICC estimates, and SIBTEST. In addition, lab members have investigated the asymptotic posterior normality of the latent trait, properties of summed scores under essential unidimensionality, the Dutch Identity, and issues related to the identifiability of latent variable models. Current research in large sample theory concerns the consistency of nonparametric maximum likelihood estimators as well as properties of item selection criteria for computerized adaptive testing.