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Falk, Carl F.; Cai, Li – Grantee Submission, 2015
In this paper, we present a flexible full-information approach to modeling multiple userdefined response styles across multiple constructs of interest. The model is based on a novel parameterization of the multidimensional nominal response model that separates estimation of overall item slopes from the scoring functions (indicating the order of…
Descriptors: Response Style (Tests), Item Response Theory, Outcome Measures, Models
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Falk, Carl F.; Cai, Li – Grantee Submission, 2014
We present a semi-parametric approach to estimating item response functions (IRF) useful when the true IRF does not strictly follow commonly used functions. Our approach replaces the linear predictor of the generalized partial credit model with a monotonic polynomial. The model includes the regular generalized partial credit model at the lowest…
Descriptors: Maximum Likelihood Statistics, Item Response Theory, Computation, Simulation