Improving the Discriminant Validation of Multi-Item Scales

Discriminant validation examines to what extent constructs measured with multi-item scales, which are hypothesized to be conceptually distinct, are empirically distinct. A literature review of published scale development studies shows that a variety of criteria and approaches to assess discriminant validity are in use. However, the requirements for an appropriate criterion have not been spelled out, which has led to the use of problematic criteria. The present research introduces three requirements that an appropriate discriminant validation criterion should satisfy, concerning the correlation, comparison standard, and comparison method. It shows that the common Fornell–Larcker criterion is based on an inappropriate comparison standard and method and that alternative criteria have weaknesses as well. The authors therefore propose an improved comparison standard, congeneric reliability, and develop a systematic discriminant validation procedure based on congeneric reliability and the existing phi criterion, both of which satisfy the three requirements. The procedure provides continuous measures of support for discriminant validity and accounts for measurement and sampling error. A detailed case study and reanalyses of seven published scale development articles demonstrate the application and strengths of the procedure. Example code and an online application facilitate its implementation.

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Publication Details

Journal
Journal of Marketing Research
Published
2025-10-03
DOI
https://doi.org/10.1177/00222437251388994
Primary Topic
Advanced Statistical Modeling Techniques
Type
article
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article

Improving the Discriminant Validation of Multi-Item Scales

Constant Pieters, Hans Baumgartner, Rik Pieters
Journal of Marketing Research
Advanced Statistical Modeling Techniques
article

Improving the Discriminant Validation of Multi-Item Scales

Constant Pieters, Hans Baumgartner, Rik Pieters
article en

Abstract

Discriminant validation examines to what extent constructs measured with multi-item scales, which are hypothesized to be conceptually distinct, are empirically distinct. A literature review of published scale development studies shows that a variety of criteria and approaches to assess discriminant validity are in use. However, the requirements for an appropriate criterion have not been spelled out, which has led to the use of problematic criteria. The present research introduces three requirements that an appropriate discriminant validation criterion should satisfy, concerning the correlation, comparison standard, and comparison method. It shows that the common Fornell–Larcker criterion is based on an inappropriate comparison standard and method and that alternative criteria have weaknesses as well. The authors therefore propose an improved comparison standard, congeneric reliability, and develop a systematic discriminant validation procedure based on congeneric reliability and the existing phi criterion, both of which satisfy the three requirements. The procedure provides continuous measures of support for discriminant validity and accounts for measurement and sampling error. A detailed case study and reanalyses of seven published scale development articles demonstrate the application and strengths of the procedure. Example code and an online application facilitate its implementation.

Journal of Marketing Research
Openalex Percentile: Top 68%
Advanced Statistical Modeling Techniques
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