University of Illinois Urbana-Champaign

Disentangling substantive responses from faking: Statistical and practical performance of the Bayesian Retrieve-Edit-Select model

Zhang, Bo

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https://hdl.handle.net/2142/108731

Description

Title
Disentangling substantive responses from faking: Statistical and practical performance of the Bayesian Retrieve-Edit-Select model
Author(s)
Zhang, Bo
Issue Date
2020-07-23
Director of Research (if dissertation) or Advisor (if thesis)
Drasgow, Fritz
Doctoral Committee Chair(s)
Drasgow, Fritz
Committee Member(s)
  • Anderson, Carolyn J
  • Newman, Daniel A
  • Kern, Justin L
  • Roberts, Brent W
Department of Study
Psychology
Discipline
Psychology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • Faking
  • Personality
  • RES
  • Bayesian
Abstract
Faking has been a major concern for the use of personality tests in high-stakes conditions because it poses a threat to the validity of selection decisions. Despite decades of efforts, researchers have neither reached a consensual understanding of the nature of faking, nor come up with effective ways to identify fakers or correct for faking. This dissertation added to the faking literature a theory-based psychometric approach – the Retrieve-Edit-Select (RES; Böckenholt, 2014) model – that can provide faking-free estimates of personality. Specifically, I first derived four variants of the original RES model that may be better suited for personality tests and developed a Bayesian algorithm to estimate these models. Then I conducted a Monte Carlo simulation study (Study 1) and an empirical study (Study 2) to examine the statistical and practical performance of the RES models. Study 1 showed that the RES models, especially the faking-free personality scores, can be estimated accurately in most conditions. Study 2 employed a within-subjects design and two different samples (real job applicants and Mturk respondents). However, I did not find unequivocal support for the empirical utility of the RES model in the two empirical datasets. Potential reasons for the lack of support, limitations and future directions are discussed.
Graduation Semester
2020-08
Type of Resource
Thesis
Permalink
http://hdl.handle.net/2142/108731
Copyright and License Information
Copyright 2020 Bo Zhang

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