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On the evaluation of structural equation models
Richard P. Bagozzi,Youjae Yi +1 more
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TLDR
In this article, structural equation models with latent variables are defined, critiqued, and illustrated, and an overall program for model evaluation is proposed based upon an interpretation of converging and diverging evidence.Abstract:
Criteria for evaluating structural equation models with latent variables are defined, critiqued, and illustrated. An overall program for model evaluation is proposed based upon an interpretation of converging and diverging evidence. Model assessment is considered to be a complex process mixing statistical criteria with philosophical, historical, and theoretical elements. Inevitably the process entails some attempt at a reconcilation between so-called objective and subjective norms.read more
Citations
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Possible determinants of consumers’ adoption of electronic grocery shopping in the Netherlands
Peter C. Verhoef,Fred Langerak +1 more
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Antecedents and outcomes of consumer environmentally-friendly attitudes and behaviour
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Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience
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University students' academic performance: An integrative conceptual framework and empirical analysis
TL;DR: This study provides support for the key mediational role of study strategies in the effect of achievement goals and self-efficacy on academic performance.
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An analysis of antecedents and consequences of trust in a corporate brand
TL;DR: In this paper, the authors present a comprehensive framework for understanding consumer trust in a corporate brand, incorporating both the antecedents and consequences of trust, and also seek to account explicitly for the differences in antecedent and consequences found among customers and among non-customers.
References
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Journal ArticleDOI
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Claes Fornell,David F. Larcker +1 more
TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
Journal ArticleDOI
A new look at the statistical model identification
TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Journal ArticleDOI
Estimating the Dimension of a Model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Estimating the dimension of a model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Journal ArticleDOI
Significance tests and goodness of fit in the analysis of covariance structures
TL;DR: In this article, a general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models, and the importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models.
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