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Structural Equation Modelling: Guidelines for Determining Model Fit

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TLDR
In this article, a selection of fit indices that are widely regarded as the most informative indices available to researchers is presented, along with guidelines on their use and strategies for their use.
Abstract
The following paper presents current thinking and research on fit indices for structural equation modelling. The paper presents a selection of fit indices that are widely regarded as the most informative indices available to researchers. As well as outlining each of these indices, guidelines are presented on their use. The paper also provides reporting strategies of these indices and concludes with a discussion on the future of fit indices.

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Path Analysis Associations Between Perceived Social Support, Stressful Life Events and Other Psychosocial Risk Factors During Pregnancy and Preterm Delivery

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Social identification, exercise participation, and positive exercise experiences: Evidence from parkrun

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References
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Journal ArticleDOI

Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives

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...
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.
Book

Principles and Practice of Structural Equation Modeling

TL;DR: The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
Journal ArticleDOI

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.