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On the evaluation of structural equation models

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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.

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Citations
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Enhancing perceived interactivity through network externalities: An empirical study on micro-blogging service satisfaction and continuance intention

TL;DR: This study examines how network externalities, in terms of perceived network size and perceived complementarity, enhance micro-blogging service users' perceived interactivity, and how such perception of interactivity influences their satisfaction and continuance intention.
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Exploring factors that influence knowledge sharing behavior via weblogs

TL;DR: A new perspective on the mechanisms related to the sharing culture construct is offered, which facilitates weblog knowledge sharing behaviors and yields important implications for understanding knowledge sharing behavior in online communities.
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Building long-term orientation in buyer–supplier relationships: The moderating role of culture

TL;DR: In this paper, the authors investigate buyer-supplier relationships in international markets and propose that the relative effects of trust and performance on long-term orientation are moderated by culture, specifically individualism and collectivism.
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An Investigation of Innovation in Nonprofit Organizations: The Role of Organizational Mission:

TL;DR: In this article, two studies were conducted among nonprofit hospitals in the United States to investigate the role of the nonprofit organization's mission in the innovation process, and the findings indicate that a clear, motivating organizational mission helps an organization to focus its attention on those innovations that will most likely support the accomplishment of that mission.
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Investigating antecedents and consequences of brand identification

TL;DR: In this paper, a theoretical model is developed and tested with a sample of car owners in the UK of two global car brands to analyse the influences of prestige, satisfaction, and communication on brand identification and to show how brand identification influences word-of-mouth and brand repurchase.
References
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Journal ArticleDOI

Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

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...
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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.
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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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