Mixed-Keying or Desirability-Matching in the Construction of Forced-Choice Measures? An Empirical Investigation and Practical Recommendations

Mengtong Li, Bo Zhang, Lingyue Li, Tianjun Sun, Anna Brown

Research output: Contribution to journalArticlepeer-review

Abstract

Forced-choice (FC) measures are becoming increasingly popular as an alternative to single-statement (SS) measures. However, to ensure the practical usefulness of an FC measure, it is crucial to address the tension between psychometric properties and faking resistance by balancing mixed keying and social desirability matching. It is currently unknown from an empirical perspective whether the two design criteria can be reconciled, and how they impact respondent reactions. By conducting a two-wave experimental design, we constructed four FC measures with varying degrees of mixed-keying and social desirability matching from the same statement pool and investigated their differences in terms of psychometric properties, faking resistance, and respondent reactions. Results showed that all FC measures demonstrated comparable reliability and induced similar respondent reactions. Forced-choice measures with stricter social desirability matching were more faking resistant, while FC measures with more mixed keyed blocks had higher convergent validity with the SS measure and displayed similar discriminant and criterion-related validity profiles as the SS benchmark. More importantly, we found that it is possible to strike a balance between social desirability matching and mixed keying, such that FC measures can have adequate psychometric properties and faking resistance. A seven-step recommendation and a tutorial based on the autoFC R package were provided to help readers construct their own FC measures.

Original languageEnglish (US)
JournalOrganizational Research Methods
DOIs
StateAccepted/In press - 2024

Keywords

  • faking
  • forced-choice
  • mixed-keying
  • social desirability matching

ASJC Scopus subject areas

  • General Decision Sciences
  • Strategy and Management
  • Management of Technology and Innovation

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