Internet Research· 2019Q1
Heuristics versus statistics in discriminant validity testing: a comparison of four procedures
- 1,823citations
- Q1SCImago
- 2019year
Short summary
The heterotrait–monotrait (HTMT) ratio and the constrained PHI approach are robust estimators of construct correlations, performing similarly in simulation studies across various conditions.
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Key points
- HTMT ratio and constrained PHI approach are robust estimators of construct correlations.
- Both methods exhibit similar performance across varied simulation conditions (construct correlations, sample sizes, indicator patterns).
- The study identified specific scenarios where both HTMT and PHI fail.
- An alternative criterion for discriminant validity testing is suggested.
AI-generated from the title and abstract; the full text is not read.
Abstract
Purpose The purpose of this paper is to review and extend recent simulation studies on discriminant validity measures, contrasting the use of cutoff values (i.e. heuristics) with inferential tests. Design/methodology/approach Based on a simulation study, which considers different construct correlations, sample sizes, numbers of indicators and loading patterns, the authors assess each criterion’s sensitivity to type I and type II errors. Findings The findings of the simulation study provide further evidence for the robustness of the heterotrait–monotrait (HTMT) ratio of correlations criterion as an estimator of disattenuated (perfectly reliable) correlations between constructs, whose performance parallels that of the standard constrained PHI approach. Furthermore, the authors identify situations in which both methods fail and suggest an alternative criterion. Originality/value Addressing the limitations of prior simulation studies, the authors use both directional comparisons (i.e. heuristics) and inferential tests to facilitate the comparison of the HTMT and PHI methods. Furthermore, the simulation considers criteria that have not been assessed in prior research.
The authors' abstract, as published at the source. Internet Research, 2019 · DOI ↗
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Field: Statistics and Probability
Statistics and ProbabilityMathematics