A1 Journal article (refereed)
An Updated Guideline for Assessing Discriminant Validity (2022)
Rönkkö, M., & Cho, E. (2022). An Updated Guideline for Assessing Discriminant Validity. Organizational Research Methods, 25(1), 6-14. https://doi.org/10.1177/1094428120968614
JYU authors or editors
Publication details
All authors or editors: Rönkkö, Mikko; Cho, Eunseong
Journal or series: Organizational Research Methods
ISSN: 1094-4281
eISSN: 1552-7425
Publication year: 2022
Publication date: 23/11/2020
Volume: 25
Issue number: 1
Pages range: 6-14
Publisher: SAGE Publications
Publication country: United States
Publication language: English
DOI: https://doi.org/10.1177/1094428120968614
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/73510
Abstract
Discriminant validity was originally presented as a set of empirical criteria that can be assessed from multitrait-multimethod (MTMM) matrices. Because datasets used by applied researchers rarely lend themselves to MTMM analysis, the need to assess discriminant validity in empirical research has led to the introduction of numerous techniques, some of which have been introduced in an ad hoc manner and without rigorous methodological support. We review various definitions of and techniques for assessing discriminant validity and provide a generalized definition of discriminant validity based on the correlation between two measures after measurement error has been considered. We then review techniques that have been proposed for discriminant validity assessment, demonstrating some problems and equivalencies of these techniques that have gone unnoticed by prior research. After conducting Monte Carlo simulations that compare the techniques, we present techniques called CICFA(sys) and χ2(sys) that applied researchers can use to assess discriminant validity.
Keywords: organisational research; quantitative research; measurement; statistical methods; factor analysis; validation; Monte Carlo methods
Free keywords: discriminant validity; Monte Carlo simulation; measurement; confirmatory factor analysis; validation; average variance extracted; heterotrait-monotrait ratio; cross-loadings
Contributing organizations
Related projects
- Measurement and modeling practices in business research – problems and solutions
- Rönkkö, Mikko
- Academy of Finland
Ministry reporting: Yes
Reporting Year: 2022
Preliminary JUFO rating: 3