Forced-choice personality measurement to reduce faking in personnel selection: Predicting block and scale fakability
Li, Mengtong
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Permalink
https://hdl.handle.net/2142/125780
Description
Title
Forced-choice personality measurement to reduce faking in personnel selection: Predicting block and scale fakability
Author(s)
Li, Mengtong
Issue Date
2024-07-03
Director of Research (if dissertation) or Advisor (if thesis)
Newman, Daniel A.
Doctoral Committee Chair(s)
Newman, Daniel A.
Zhang, Bo
Committee Member(s)
Drasgow, Fritz
Kern, Justin
Zhang, Susu
Department of Study
Psychology
Discipline
Psychology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
forced-choice
faking
HEXACO
personality
Abstract
When measuring personality for personnel selection, forced-choice (FC) personality measures are often able to alleviate faking that plagues traditional Likert-type single-statement (SS) measures. However, most previous studies provided limited information about faking resistance of the FC measure at the block level, or about block-level attributes that can mitigate faking effects. Such information would be useful for the construction of faking-resistant scales. Using forced-choice measures constructed from the HEXACO-200 item pool, the current study examined possible factors influencing the fakability of FC blocks (as modeled upon the faking mixture model developed by Frick [2022]) and fakability of the whole FC measure. These factors include block size, social desirability matching stringency, overall block desirability, and response format (RANK vs. most-and-least like me: MOLE). Results suggested larger block sizes may correspond to lower fakability. Further, the effect of block size on mitigating block fakability was stronger for MOLE response formats (compared to RANK formats), and was stronger when overall block desirability was low. The overarching aim is to contribute toward the development of psychometrically robust and faking-resistant personality measures.
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