A1 Journal article (refereed)
An Updated Guideline for Assessing Discriminant Validity (2020)


Rönkkö, Mikko; Cho, Eunseong (2020). An Updated Guideline for Assessing Discriminant Validity. Organizational Research Methods, OnlineFirst. DOI: 10.1177/1094428120968614


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Publication details

All authors or editors: Rönkkö, Mikko; Cho, Eunseong

Journal or series: Organizational Research Methods

ISSN: 1094-4281

eISSN: 1552-7425

Publication year: 2020

Volume: OnlineFirst

Publisher: SAGE Publications

Publication country: United States

Publication language: English

DOI: https://doi.org/10.1177/1094428120968614

Open Access: Open access publication published in a hybrid channel

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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


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Last updated on 2021-08-03 at 08:48