Open Access
Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures.
Karin Schermelleh-Engel,Helfried Moosbrugger,Hans Müller +2 more
- Vol. 8, pp 23-74
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TLDR
Some guidelines that should help applied researchers to evaluate the adequacy of a given structural equation model are provided.Abstract:
For structural equation models, a huge variety of fit indices has been developed. These indices, however, can point to conflicting conclusions about the extent to which a model actually matches the observed data. The present article provides some guidelines that should help applied researchers to evaluate the adequacy of a given structural equation model. First, as goodness-of-fit measures depend on the method used for parameter estimation, maximum likelihood (ML) and weighted least squares (WLS) methods are introduced in the context of structural equation modeling. Then, the most common goodness-of-fit indices are discussed and some recommendations for practitioners given. Finally, we generated an artificial data set according to a "true" model and analyzed two misspecified and two correctly specified models as examples of poor model fit, adequate fit, and good fit.read more
Citations
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Construction and factorial validation of a short form of the Self-Compassion Scale.
TL;DR: The SCS-SF represents a reliable and valid alternative to the long-form SCS, especially when looking at overall self-compassion scores.
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Reporting practices in confirmatory factor analysis: an overview and some recommendations.
TL;DR: Results indicate some positive findings with respect to reporting practices including proposing multiple models a priori and near universal reporting of the chi-square significance test, but many deficiencies were found such as lack of information regarding missing data and assessment of normality.
Book
Structural Equation Modeling and Natural Systems
TL;DR: In this article, structural equation models with observed variables were used to understand plant diversity patterns in ecological communities, and they were applied to understand the temporal dynamics of a plant-insect interaction.
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Microbial diversity drives multifunctionality in terrestrial ecosystems
Manuel Delgado-Baquerizo,Fernando T. Maestre,Peter B. Reich,Peter B. Reich,Thomas C. Jeffries,Juan José Gaitán,Daniel Encinar,Miguel Berdugo,Colin Campbell,Brajesh K. Singh +9 more
TL;DR: The findings provide empirical evidence that any loss in microbial diversity will likely reduce multifunctionality, negatively impacting the provision of services such as climate regulation, soil fertility and food and fibre production by terrestrial ecosystems.
References
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Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives
Li-tze Hu,Peter M. Bentler +1 more
TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
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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.
Book
An introduction to the bootstrap
Bradley Efron,Robert Tibshirani +1 more
TL;DR: This article presents bootstrap methods for estimation, using simple arguments, with Minitab macros for implementing these methods, as well as some examples of how these methods could be used for estimation purposes.
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Alternative Ways of Assessing Model Fit
Michael W. Browne,Robert Cudeck +1 more
TL;DR: In this paper, two types of error involved in fitting a model are considered, error of approximation and error of fit, where the first involves the fit of the model, and the second involves the model's shape.
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Comparative fit indexes in structural models
TL;DR: A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models and two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes.