Estimating and Evaluating Convergent and Discriminant Validity Evidence 257 correlated with those crucial variables, test developers and test users gain increased confidence in the test. Sci. Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. Mark. Abstract. A new criterion for assessing discriminant validity in variance-based structural equation modeling. References. Fornell and Larcker criterion is the most widely used method for this purpose. Those correlations, sometimes called . In quantitative research, you have to consider the reliability and validity of your methods and measurements.. Validity tells you how accurately a method measures something. Discriminant Validity Assessment Abstract. For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). Published on September 6, 2019 by Fiona Middleton. validity coefficients, are fundamental for establishing validity. Sci. 43 [1]: 115-135 January 2015) is the hottest paper in the field of Economics & Business for the period ending October 31, 2016. A new criterion for assessing discriminant validity in variance-based structural equation modeling A new criterion for assessing discriminant validity in variance-based structural equation modeling Henseler, Jörg; Ringle, Christian; Sarstedt, Marko 2014-08-22 00:00:00 J. of the Acad. Revised on June 19, 2020. (2015) 43:115â135 DOI 10.1007/s11747-014-0403-8 METHODOLOGICAL PAPER A new criterion â¦ For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. Assessment of discriminant validity is a must in any research that involves latent variables for the prevention of multicollinearity issues. A new criterion for assessing discriminant validity in variance-based structural equation modeling. Mark. However, a new method has emerged for establishing the discriminant validity assessment through heterotrait-monotrait (HTMT) ratio of correlations method. If research reveals that a testâs validity coef- However, two conclusions that are new to discriminant validity literature can be drawn: First, the lack of cross-loadings in the population (i.e., factorial validity) is not a strict prerequisite for discriminant validity assessment as long as the cross-loadings are modeled appropriately. Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). The four types of validity. Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. Abstract. The discriminant validity assessment has the goal to ensure that a reflective construct has the strongest relationships with its own indicators (e.g., in comparison with than any other construct) in the PLS path model (Hair et al., 2017). For variance-based structural equation modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. Our latest report of New Hot Papers in Essential Science Indicators shows that the paper âA new criterion for assessing discriminant validity in variance-based structural equation modeling,â (J. Acad.