Journal
ORGANIZATIONAL RESEARCH METHODS
Volume 25, Issue 1, Pages 6-47Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/1094428120968614
Keywords
discriminant validity; Monte Carlo simulation; measurement; confirmatory factor analysis; validation; average variance extracted; heterotrait-monotrait ratio; cross-loadings
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Funding
- Academy of Finland [311309]
- Kwangwoon University
- Academy of Finland (AKA) [311309, 311309] Funding Source: Academy of Finland (AKA)
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This study reviews the definitions and techniques for assessing discriminant validity and proposes a generalized definition. After conducting Monte Carlo simulations, the study presents techniques called CICFA(sys) and chi(2)(sys) that applied researchers can use to evaluate discriminant validity.
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 chi(2)(sys) that applied researchers can use to assess discriminant validity.
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