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HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling
by
Roemer, Ellen
, Henseler, Jörg
, Schuberth, Florian
in
Computer Science Applications
/ Confidence
/ Confidence intervals
/ Criteria
/ Design factors
/ Discriminant validity
/ Equivalence
/ Heuristic
/ Industrial and Manufacturing Engineering
/ Industrial relations
/ Management Information Systems
/ Measurement model assessment
/ Monte Carlo simulation
/ Multivariate statistical analysis
/ Statistical inference
/ Strategy and Management
/ Structural equation modeling
/ Structural equation modeling (SEM)
/ Validation studies
/ Validity
2021
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HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling
by
Roemer, Ellen
, Henseler, Jörg
, Schuberth, Florian
in
Computer Science Applications
/ Confidence
/ Confidence intervals
/ Criteria
/ Design factors
/ Discriminant validity
/ Equivalence
/ Heuristic
/ Industrial and Manufacturing Engineering
/ Industrial relations
/ Management Information Systems
/ Measurement model assessment
/ Monte Carlo simulation
/ Multivariate statistical analysis
/ Statistical inference
/ Strategy and Management
/ Structural equation modeling
/ Structural equation modeling (SEM)
/ Validation studies
/ Validity
2021
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Do you wish to request the book?
HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling
by
Roemer, Ellen
, Henseler, Jörg
, Schuberth, Florian
in
Computer Science Applications
/ Confidence
/ Confidence intervals
/ Criteria
/ Design factors
/ Discriminant validity
/ Equivalence
/ Heuristic
/ Industrial and Manufacturing Engineering
/ Industrial relations
/ Management Information Systems
/ Measurement model assessment
/ Monte Carlo simulation
/ Multivariate statistical analysis
/ Statistical inference
/ Strategy and Management
/ Structural equation modeling
/ Structural equation modeling (SEM)
/ Validation studies
/ Validity
2021
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HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling
Journal Article
HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling
2021
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Overview
PurposeOne popular method to assess discriminant validity in structural equation modeling is the heterotrait-monotrait ratio of correlations (HTMT). However, the HTMT assumes tau-equivalent measurement models, which are unlikely to hold for most empirical studies. To relax this assumption, the authors modify the original HTMT and introduce a new consistent measure for congeneric measurement models: the HTMT2.Design/methodology/approachThe HTMT2 is designed in analogy to the HTMT but relies on the geometric mean instead of the arithmetic mean. A Monte Carlo simulation compares the performance of the HTMT and the HTMT2. In the simulation, several design factors are varied such as loading patterns, sample sizes and inter-construct correlations in order to compare the estimation bias of the two criteria.FindingsThe HTMT2 provides less biased estimations of the correlations among the latent variables compared to the HTMT, in particular if indicators loading patterns are heterogeneous. Consequently, the HTMT2 should be preferred over the HTMT to assess discriminant validity in case of congeneric measurement models.Research limitations/implicationsHowever, the HTMT2 can only be determined if all correlations between involved observable variables are positive.Originality/valueThis paper introduces the HTMT2 as an improved version of the traditional HTMT. Compared to other approaches assessing discriminant validity, the HTMT2 provides two advantages: (1) the ease of its computation, since HTMT2 is only based on the indicator correlations, and (2) the relaxed assumption of tau-equivalence. The authors highly recommend the HTMT2 criterion over the traditional HTMT for assessing discriminant validity in empirical studies.
Publisher
Emerald Publishing Limited,Emerald Group Publishing Limited
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