Extreme Response Style: Which Model Is Best?

Autor/in	Leventhal, Brian
Titel	Extreme Response Style: Which Model Is Best?
Quelle	(2017), (180 Seiten) PDF als Volltext Verfügbarkeit Ph.D. Dissertation, University of Pittsburgh
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
ISBN	978-0-3551-9110-3
Schlagwörter	Hochschulschrift; Dissertation; Psychometrics; Item Response Theory; Simulation; Models; Scores; Likert Scales; Goodness of Fit; Evaluation Methods; Sample Size; Generalization; Error of Measurement + Suchen Sie Ihr Suchwort? Thesis; Dissertations; Academic thesis; Psychometry; Psychometrie; Item-Response-Theorie; Simulation program; Simulationsprogramm; Analogiemodell; Likert-Skala; Messfehler
Abstract	More robust and rigorous psychometric models, such as multidimensional Item Response Theory models, have been advocated for survey applications. However, item responses may be influenced by construct-irrelevant variance factors such as preferences for extreme response options. Through empirical and simulation methods, this study evaluates the use of the IRTree Model, the multidimensional nominal response model, and the modified generalized partial credit model designed to account for extreme response tendencies. The modified generalized partial credit model was found to have the best overall fit in terms of test-level, item-level, and person-level posterior predictive model checks performed. Estimation of this model also resulted in the lowest mean squared error between observed total score and expected total score. The multidimensional nominal response model had the lowest deviance information criterion among the three models. The empirical study, data validation from the simulation study, and the simulation results provided evidence that the IRTree Model was measuring a unique construct-irrelevant variance factor compared to the two other methods. For all simulation conditions of sample size (500, 1000), survey length (10, 20), and number of response options (4, 6), the modified generalized partial credit model had the most adequate model fit with respect to mean item mean squared error. The multidimensional nominal response model was found equally suitable for surveys measuring one substantive trait when responses to 10 4-option forced-choice Likert-type items were explored. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.] (As Provided).
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Update	2020/1/01