Linear Versus Models in Item Response Theory

Randomized Item Response Theory Models

The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR technique links the observed item response with the tr...

Linear Item Response Theory, Nonlinear Item Response Theory, and Factor Analysis: A Unified Framework

What it is now known as item response modeling [for an overview see van der Linden and Hambleton (1997)] originated as an effort to overcome the limitations of the factor model when applied to test items. Test items are most often categorical in nature, whereas the factor model was designed for continuous data. Unfortunately, over the years item response modeling and factor modeling have develo...

Testing Linear Models for Ability Parameters in Item Response Models.

Methods for testing hypotheses concerning the regression parameters in linear models for the latent person parameters in item response models are presented. Three tests are outlined: A likelihood ratio test, a Lagrange multiplier test and a Wald test. The tests are derived in a marginal maximum likelihood framework. They are explicitly formulated for the 3-parameter logistic model, but it is sh...

Validating Item Response Theory Models in Simulated Environments

Item Response Theory

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