Title

The Influence of Dimensionality on Parameter Estimation Accuracy in the Generalized Graded Unfolding Model

Authors

Authors

N. T. Carter;M. J. Zickar

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

Educ. Psychol. Meas.

Keywords

Item response theory; unfolding; multidimensionality; Monte Carlo; simulation; LOCAL ITEM DEPENDENCE; LOGISTIC MODEL; PERFORMANCE; Psychology, Educational; Mathematics, Interdisciplinary Applications; Psychology, Mathematical

Abstract

The generalized graded unfolding model (GGUM) is an ideal point model of responding that is consistent with the Thurstonian theory of respondent behavior. Ideal point models have recently generated interest in the realms of attitude and personality assessment. One unclear aspect of applying ideal point models is the influence of multidimensionality on GGUM item and person parameters estimation accuracy. Using simulated data, the authors tested the influence of the balance, or ratio, of items loading onto two dimensions, the degree of bidimensionality and sample size on parameter estimation accuracy. The results suggest that bidimensionality and the proportion of items loading onto a second trait increases estimation error. The second trait was chosen in estimation when a large number of the items in the survey reflected a highly irrelevant second trait. Estimation error was greater for persons and items at the extreme ends of the continuum; positive estimates were biased upward and positive parameters downward. The results suggest that although the GGUM chooses another trait in estimation, in most cases conventional fit analyses and checks for item parameter extremity are likely to be successful in identifying items measuring another trait. Furthermore, the conditions in which the trait being estimated may not be clear should be rare in practice. The implications of these results for researchers who wish to apply these models to real-life data are discussed.

Journal Title

Educational and Psychological Measurement

Volume

71

Issue/Number

5

Publication Date

1-1-2011

Document Type

Article

Language

English

First Page

765

Last Page

788

WOS Identifier

WOS:000295322400002

ISSN

0013-1644

Share

COinS