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Journal ArticleDOI

Assessing the Hypothesis of Measurement Invariance in the Context of Large-Scale International Surveys.

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TLDR
This article used data from one large-scale survey as a basis for examining the extent to which typical fit measures used in multiple-group confirmatory factor analysis are suitable for detecting measurement invariance in a large scale survey context.
Abstract
In the field of international educational surveys, equivalence of achievement scale scores across countries has received substantial attention in the academic literature; however, only a relatively recent emphasis on scale score equivalence in nonachievement education surveys has emerged. Given the current state of research in multiple-group models, findings regarding these recent measurement invariance investigations were supported with research that was limited in scope to few groups and relatively small sample sizes. To that end, this study uses data from one large-scale survey as a basis for examining the extent to which typical fit measures used in multiple-group confirmatory factor analysis are suitable for detecting measurement invariance in a large-scale survey context. Using measures validated in a smaller scale context and an empirically grounded simulation study, our findings indicate that many typical measures and associated criteria are either unsuitable in a large group and varied sample-siz...

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Citations
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Journal ArticleDOI

Measurement invariance conventions and reporting: The state of the art and future directions for psychological research

TL;DR: The state of measurement invariance testing and reporting is surveyed, the results of a literature review of studies that tested invariance are details, and Implications for the future of measurement symmetry testing, reporting, and best practices are discussed.

measurement and evaluation in counseling and Development

TL;DR: In this article, Aviles et al. present a review of the state of the art in the field of test data analysis, which includes the following institutions: Stanford University, Stanford Graduate School of Education, Stanford University and the University of Southern California.
Journal ArticleDOI

What to do when scalar invariance fails: The extended alignment method for multi-group factor analysis comparison of latent means across many groups.

TL;DR: Alignment augmented by AwC provides applied researchers from diverse disciplines considerable flexibility to address substantively important issues when the traditional CFA-MI scalar model does not fit the data.
Journal ArticleDOI

Multiple-Group Invariance with Categorical Outcomes Using Updated Guidelines: An Illustration Using Mplus and the lavaan/semTools Packages

TL;DR: The current state of categorical ME/I is described and an up-to-date method for model identification and invariance testing is demonstrated and exemplified via multiple-group confirmatory factor analysis using Mplus and the lavaan and semTools packages in R.
Journal ArticleDOI

A primer to (cross-cultural) multi-group invariance testing possibilities in R.

TL;DR: A general introduction to invariance testing and a tutorial of three major classes of techniques that can be easily implemented in the free software and statistical language R are provided.
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...
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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.
Book

Structural Equations with Latent Variables

TL;DR: The General Model, Part I: Latent Variable and Measurement Models Combined, Part II: Extensions, Part III: Extensions and Part IV: Confirmatory Factor Analysis as discussed by the authors.
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.
Journal ArticleDOI

Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance

TL;DR: In this paper, the authors examined the change in the goodness-of-fit index (GFI) when cross-group constraints are imposed on a measurement model and found that the change was independent of both model complexity and sample size.
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