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Autor/inn/en | Roberts, James S.; Donoghue, John R.; Laughlin, James E. |
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Titel | Estimating Parameters in the Generalized Graded Unfolding Model: Sensitivity to the Prior Distribution Assumption and the Number of Quadrature Points Used. |
Quelle | (1999), (34 Seiten)
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Monographie |
Schlagwörter | Attitude Measures; Estimation (Mathematics); Item Response Theory; Simulation |
Abstract | The generalized graded unfolding model (J. Roberts, J. Donoghue, and J. Laughlin, 1998, 1999) is an item response theory model designed to unfold polytomous responses. The model is based on a proximity relation that postulates higher levels of expected agreement with a given statement to the extent that a respondent is located close to the statement on a unidimensional latent continuum. J. Roberts and others (1998) have examined the recovery of item and person parameters from the generalized graded unfolding model. Item and person parameters were estimated. This study used simulation methods to assess the sensitivity of model parameters to the prior distribution used in these estimation procedures. It also examined the effects of the number of quadrature points used in the numerical integration process and the calibration sample on the accuracy of the resulting parameter estimates. The results show that item parameter estimated derived from the marginal maximum likelihood procedure were fairly robust to discrepancies between the prior and true distributions of person parameters. Consequently, the person parameter estimates derived from the expected a posteriori procedure were generally robust as well, except for those individuals with the most extreme response patterns. The results also indicate that 20 quadrature points are adequate for the accurate recovery of model parameters. These findings will help establish the utility of the generalized graded unfolding model in applied measurement situations and will promote the use of item response theory in the attitude/preference measurement domain. (Contains 2 tables, 14 figures and 19 references.) (Author/SLD) |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |