Education and Human Sciences, College of (CEHS)
First Advisor
Kurt Geisinger
Date of this Version
Summer 5-2023
Citation
Beck, M. F. (2023). The examination of nonparametric person-fit statistics as appropriate measures of response bias in ordered polytomous items [Unpublished doctoral dissertation]. University of Nebraska-Lincoln
Abstract
Survey research is ubiquitous within the social sciences; however, surveys are vulnerable to response biases. Response biases introduce construct-irrelevant variance into survey responses, which degrades the accuracy of conclusions drawn through the use of surveys. Nonparametric person-fit statistics have been shown to accurately identify response biases in dichotomous response data but are not well studied in polytomous response data. This study examines the accuracy of nonparametric person-fit statistics in polytomous response data. A 6 x 4 x 4 x 2 simulation study was conducted, with type of aberrancy (6), number of response options (4), dimensionality (4), and test length (2) as factors. The sensitivity, specificity, positive predictive value, and negative predictive value for U3, the normed number of Guttman errors, and HTi were calculated using a bootstrapped cutoff. Findings indicate that these person-fit statistics with a conservative cutoff had excellent specificity but poor sensitivity.
Advisor: Kurt F. Geisinger
Comments
A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Doctor of Philosophy, Major: Psychological Studies in Education (Quantitative, Qualitative, and Psychometric Methods), Under the Supervision of Professor Kurt F. Geisinger. Lincoln, Nebraska: May 2023
Copyright © 2023 Mark F. Beck