A General Item Response Theory Model for Unfolding Unidimensional Polytomous Responses

By J. S. Roberts, J. Donoghue, J. Laughlin. 2000

326 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/aea36475c5adaf37af5dfedcdbdf3b07f90f27aa

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Markov Chain Monte Carlo Estimation of Item Parameters for the Generalized Graded Unfolding Model (2006, methodology): “In this article, the authors develop an MCMC algorithm for a recently introduced ideal point model, the GGUM (Roberts et al., 2000), which is flexible in its assumptions and has been shown to provide good fit to personality data in recent studies (Stark, Chernyshenko, Drasgow, & Williams, in press).”
Characteristics of MML/EAP Parameter Estimates in the Generalized Graded Unfolding Model (2002, methodology): “The generalized graded unfolding model (GGUM) is a very general, unidimensional parametric item response theory (IRT) model for unfolding that has recently been introduced by Roberts, Donoghue, and Laughlin (2000).”
GGUM2004: A Windows-Based Program to Estimate Parameters in the Generalized Graded Unfolding Model (2006, methodology): “The GGUM2004 software estimates parameters of the generalized graded unfolding model (GGUM), developed by Roberts, Donoghue, and Laughlin (2000).”
An “Unfolding” Latent Variable Model for Likert Attitude Data (2007, methodology): “Other models in this class include the generalized hyperbolic cosine model (Andrich 1996; Rost and Luo 1997) and the generalized graded unfolding model (Roberts, Donoghue, and Laughlin 2000).”
The Caring‐Killing Paradox: Euthanasia‐Related Strain Among Animal‐Shelter Workers (2005, methodology): “The items were developed primarily by modifying the target content of a subset of items from an abortion attitudes scale ( Roberts, Donoghue, & Laughlin, 2000 ).”
An IRT Approach to Constructing and Scoring Pairwise Preference Items Involving Stimuli on Different Dimensions: The Multi-Unidimensional Pairwise-Preference Model (2005, methodology): “Given these results, the GGUM was chosen for illustrating the MUPP approach to scoring pairwise preferences.”
75 Years After Likert: Thurstone Was Right! (2010, methodology): “If the six intermediate items were deleted, the fits of the 2PLM and GGUM would be very similar.”